Macromodels are dependencies of the “black box” type with a reduced number of internal relations. This is most convenient to create such dependence in the form of power polynomials. Obtaining formal macromodels (FMM) as a power polynomial based on the analysis of the results of numerical experiments conducted with the help of the original mathematical models (OMM).
Therefore, the problem of formal macro modelling includes two subtasks:
1. The FMM structure determining.
2. The numerical values of the FMM parameters (polynomial coefficients) finding.
As is known, the accuracy of the polynomial and the region of its adequacy greatly depend on its structure and order. At the same time, obtaining polynomials of high degrees requires analysis of many variants of the investigated flow path elements, which leads to significant computer resources cost and complicates the process of calculating the coefficients of the polynomial.
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.
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
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!
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.
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:
Appropriate working fluid selection;
Increment of initial parameters of bottoming cycle up to supercritical values;
Maximize waste heat utilization due to the usage of low temperature heat sources;
Bottoming cycle complexification or usage of several bottoming cycles with different fluids
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.
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.
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.
The Brayton cycle is the fundamental constant pressure gas heating cycle used by all air-breathing jet engines. The Brayton cycle can be portrayed by a diagram of temperature vs. specific entropy, or T–S diagram, to visualize changes to temperature and specific entropy during a thermodynamic process or cycle. Figure 1 shows this ideal cycle as a black line. However, in the real world, the compression and expansion processes are never isentropic, and there is always a certain pressure loss in the combustor. The real Brayton cycle looks more like the blue line in Figure 1.
The four stages of this cycle are described as:
1-2: isentropic compression
2-3: constant pressure heating
3-4: isentropic expansion
4-0: constant pressure cooling (absent in open cycle gas turbines)
The most basic form of a jet engine is a turbojet engine. Figures 2a and 2b provide the basic design of a turbojet engine. It consists of a gas turbine that produces hot, high-pressure gas, but has zero net shaft power output. A nozzle converts the thermal energy of the hot, high-pressure gas at the outlet of the turbine into a high-kinetic-energy exhaust stream. The high momentum and high exit pressure of the exhaust stream result in a forward thrust on the engine. Read More
The lubrication system is one of the most important systems of an engine.
This system should ensure:
Delivery of the required oil amount to the moving parts (e.g.-Bearings);
Dissipation of the heat generated due to friction by circulation of lubricant throughout the system; and
Cleaning of the oil from contamination and impurities introduced during engine operation.
To meet the above requirements, the lubricant circulation (lubricant reaching each component) should happen at appropriate pressure and mass flow rate throughout the system. This is also required in order to avoid cavitation caused by adverse pressure, and excessive heat generation due to less mass flow rate, at any place or particularly at any component. However, sometimes lubricant does not circulate properly to each corner of the system or to the rotating components. In some cases, the rotation of the crankshaft can actually starve the bearings and increase the internal heat due to insufficient supply of lubrication.
To avoid such problems, simulation engineers must model the whole system at all operating modes. They can predict the best system by varying flow rates (volumetric or mass flow rates), system pressures, temperatures, heat flows, as well as by changing the system geometry itself. Such modelling can be performed easily and with sufficient accuracy in a 1D Thermal Fluid analysis tool, such as AxSTREAM NET™ developed by SoftInWay.
It is worthwhile to use a 1D-Analysis tool in this case, because it can be used at any stage of the system design process to explore more options for improving the final design and to reduce development cycle time. The simulation engineer can easily create a model of automotive engine lubrication system, using different elements (components) which are available in the element database of AxSTREAM NET™. The system configuration can also be easily changed at any stage in the design process without rebuilding the complex 3D models.
Let us try to understand how to build a 1D scheme for an automotive engine lubrication system in a 1D tool (AxSTREAM NET™). First, we need to identify the major elements (components) which are part of the automotive engine lubrication system as per their order or sequence in the scheme. A typical engine lubrication system involves components like Oil – sump, strainer, pump and filter, all of which are parts of the initial oil suction line. In addition, the main gallery involves components like flow passages within the connecting rods, crankshaft, and bearings. The typical connections among these elements are shown in Figure 1.
Now let’s see the arrangement of a few components with their specific purposes towards the construction of the whole model.
It is a well-known fact in the turbomachinery community that the highest temperature achievable at the inlet of the turbine is a critical performance parameter for the turbine. For any given pressure ratio and adiabatic efficiency, the turbine specific work is proportional to the inlet stagnation temperature. Typically, a 1% increase in the turbine inlet temperature can cause a 2-3% increase in the engine output.
The major limitation for the maximum achievable value of the turbine inlet temperature comes from the material used for the turbine. The maximum material temperature has to be kept in check for multiple reasons, from the physical integrity to the structural reliability, and resulting temperature needs to be less than the turbine blade material’s maximum temperature.
In today’s world where “time is money,” each and every industry involving turbomachinery wants to deliver their high performance products in the quickest time possible. Computational fluid dynamics (CFD) replaces the huge number of testing requirements thus not only shortening the design cycle time, but also reducing development costs.
Today with advancements in computational resources, numerical methods, and the availability of commercial tools, CFD has become a major tool for the design phase of a project. With a large number of validations and bench markings available on the applicability of CFD for centrifugal compressors, it has become an indispensable tool for the aerodynamic designer to verify the design and understand the flow physics inside a compressor’s flow path. However, CFD is still computationally expensive and requires a high level of user-knowledge and experience to get meaningful results. CFD analysis can be performed with and without considering viscous effects of the flow. The inclusion of viscosity into the flow introduces additional complexities for choosing the most appropriate turbulence closure model. CFD however, has some limitations due to:
– Errors created during modeling where the true physics are not well-known and are very complex to model.
– Multiple approximation and model errors created during the calculation process (such as mesh resolution, steady flow assumption, turbulence closure, geometric approximation, unknown boundary profile etc.). These approximations impact the calculations of local values of vital parameters.
In CFD for example, if the 1D design is not accurate, (stage loading and blade diffusion factors etc.), then CFD cannot turn out a good design. It is critical to use a design tool such as AxSTREAM® which can generate optimized designs with less time and effort starting from the specification.
The preliminary design modules of AxSTREAM® uses inverse design tasks to generate the initial flow path for the centrifugal compressor. By choosing the right combination of geometrical and design parameters from the start, AxSTREAM® reduces the number of design cycle iterations required in generating an accurate design.
This initial design obtained is further analyzed and optimized using throughflow solvers in AxSTREAM® which considers various operating conditions. The throughflow solvers in AxSTREAM® predict the performance parameters at different sections and stations, and presents the blade loading, flow distribution along the flow path, etc.
The generation of 3D geometry for the impeller and diffuser is another complex activity which is greatly simplified by using the radial profiler and 3D blade design module in AxSTREAM®. The geometry generated in AxSTREAM® is fully parameterized with complete control for the user to modify as and when required. Figure 1 shows a parameterized impeller geometry generated using seven spanwise sections with contours of the curvature.
In CFD analysis of turbomachines, grid generation becomes a very challenging task due to the geometries of complicated, twisted blades. To achieve reliable CFD results, the grid must resolve the topology accurately to preserve this geometric information. The quality of the grid should be in an acceptable range especially the angle, aspect ratio, and skewness of the grid elements. Automatic mesh generation tools are employed to reduce the turbomachines meshing complications. The AxSTREAM® platform uses AxCFD™ to generate a high quality mesh in considerably short time which captures the accurate flow features.
Gas turbine (GT) engines are the primary engines of modern aviation. They are also widely used as power propulsion engines for power stations. The specificity of these engines implies they frequently work at off-design/part load modes that occur with:
Different modes of aircrafts:
Ground idle mode
Maximum continuous mode
Different ambient conditions
Grid demands (for power generation engines and gas pumping (compressor) stations)
Due to the off-design/part load operating conditions, the parameters of the engines might change significantly, which influences not only the engine efficiency, but also the reliable work of the turbine (high temperature at turbine inlet) and compressor (surge zone) at joint operational points. This is why accurate predictions of the gas generator parameters are crucial at every off-design mode.
To define the joint operational point, the compressor and turbine maps which are created for specified ambient conditions can be used. For example, pressure equal 101.3kPa, temperature – 288.15K. Maps method is widely used, relatively simple and allows you to find the needed engine parameters in the shortest time. However, when cooling is present, engine operation at low power modes (ground idle) impede the accurate determination of joint operational conditions based on maps. The significant drawback to the maps based approach is that it does not give the full picture of the physical processes in turbomachine flow paths which is critical for off-design calculations.
Utilization of the digital twin concept allows significant increase of the off-design performance calculation accuracy. Use of the digital equivalent of object was introduced in 2003 . Despite this, less 1% of machines that are in use today are modeled with digital twin technology . Utilization of digital twin leads to a significant decrease in time and cost for developing and optimization of an object.
Centrifugal Pumps are the most popular and commonly used type of pump for the transfer of any type of fluid. The volumetric flow rate range of centrifugal pumps can vary from several tens of ml/hour to one hundred thousand m3/hour , while the pressure can be normal pressure to nearly 20MPa; and the liquid temperature can be as low as -200℃ or as high as 800℃. The fluid being transferred can be water (clean or sewage), oil, acid or alkali, suspension or liquid metal, etc. Therefore, centrifugal pumps are used across numerous industries:
In the oil and gas or chemical industries, converting crude oil to products requires a complex process. Pumps play an important role in transferring these liquids, providing the required pressure and flow rate for chemical reactions. Sometimes, pumps are used to adjust temperature in certain parts of the system.
In agriculture, centrifugal pumps are used in the majority of irrigation machinery. Agriculture pumps make up half of the total amount of centrifugal pumps being used today.
In mining and metallurgy industries, centrifugal pumps are the most widely used equipment, for draining, and cooling of water supplies, etc.
For power generation, the nuclear power plants need large amounts of primary, and secondary system pumps, while the thermal power plants also need boiler feed pumps, condensate pumps, loop pumps and as well as ash pumps.
In military applications, the adjusting of airplane wings and rudders, turning of turret on ships and tanks, the up and down of submarines, all rely on pumps for hydraulic fluids.
In shipbuilding, there are more than 100 different types of pumps in one typical ocean ship.
Other applications include municipal water supplies and drainage; water supplies of locomotives; lubricating and cooling of machining equipment; bleach and dye transfer of textile industry; and milk and beverage pumping and sugar refining in the food industry.
Centrifugal pumps can be classified based on the number of impellers in the pump:
A single-stage pump, with only one impeller, is commonly used for high flow and low to moderate total dynamic head, as in Figure 1.
A multi-stage pump has two or more impellers working in a series to achieve higher total dynamic head. Read More