Ejector Design Calculation Software Reason 8 Crack Mac Torrent Usb 2.0 Serial Driver Windows 10 64 Bit Actress Savithri Death Hdminicam App For Mac Tp Link Tf 3200 Driver Windows 10 Boom 3d Virtual Surround Audio For Mac Imovie 10.1.7 Free For Mac Presspercent Serial. Ejector Design, free ejector design freeware software downloads.
Ejector Design Calculation Software
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Vacworks II Selection Software Suite Vacworks II is a selection software suite developed by Graham engineers that enables you to select ejector systems or ejectors in combination with liquid ring vacuum pumps. You are able to select up to a four-stage ejector system, with or without a precondenser, that includes either surface type or direct contact inter and after condensers. The software will provide you with utility consumption, equipment size, and drawings of the individual components. It also includes useful tools for estimating vapor pressures of different organic or inorganic compounds, calculating hydraulic losses in piping systems under vacuum, determining the proper tail leg height for a vacuum condenser, a calculation routine for converting between mass and volumetric flow rate, and a conversion utility for converting between different units of measure.
Fluids is open-source software for engineers and technicians working in thefields of chemical, mechanical, or civil engineering. It includes modulesfor piping, fittings, pumps, tanks, compressible flow, open-channel flow,atmospheric properties, solar properties, particle size distributions,two phase flow, friction factors, control valves, orifice plates andother flow meters, ejectors, relief valves, and more.
Shipping ballast water can have significant ecological and economic impacts on aquatic ecosystems. Currently, water ejectors are widely used in marine applications for ballast water treatment owing to their high suction capability and reliability. In this communication, an improved ballast treatment system employing a liquid-gas ejector is introduced to clear the ballast water to reduce environmental risks. Commonly, the liquid-gas ejector uses ballast water as the primary fluid and chemical ozone as the secondary fluid. In this study, high-pressure water and air, instead of ballast water and ozone, are considered through extensive numerical and experimental research. The ejector is particularly studied by a steady three-dimensional multiphase computational fluid dynamics (CFD) analysis with commercial software ANSYS-CFX 14.5. Different turbulence models (including standard , RNG , SST, and ) with different grid size and bubble size are compared extensively and the experiments are carried out to validate the numerical design and optimization. This study concludes that the RNG turbulence model is the most efficient and effective for the ballast water treatment system under consideration and simple change of nozzle shape can greatly improve the ejector performance under high back pressure conditions.
In the conventional ozone treatment systems, ozone gas is directly bubbled into the water which decomposes and reacts with chemicals. It is very effective to kill microorganisms, but not so at killing larger organisms. In order to kill both large organisms and microorganisms, a new ozone treatment system needs to be developed. Figure 1 shows the diagram of the proposed ballast water treatment system in this work. This system still employs ozone to kill the microorganisms. However, ozone is no longer directly pumped into the ballast water but is absorbed and ejected into ballast water by an ejector (see Figure 2). Specifically, a small amount of ballast water from the main pipe is pumped as the primary fluid through the ejector to produce a lower pressure in the suction chamber of the ejector, which absorbs ozone as the secondary fluid into the ejector and then ejects it into the downstream of the main pipe to clean the ballast water. Microorganisms are killed by an appropriate mixed fluid downstream, whilst large organisms are killed by the high-velocity impact of the ejected flow. This design has advantages of high efficiency in producing intense mixing flow and a high interfacial area for generating small bubbles to rapidly treat a large volume of ballast water. However, the main disadvantage is that the efficiency of this system is strongly dependent on the performance of the ejector. If inappropriately designed or equipped with a high back pressure, the ejector will not absorb enough ozone to treat the discharged ballast water, resulting in microorganism survivals and their escape to the local water.
This ejector-based system will be used under a high back pressure condition, so its performance under high back pressure condition is of great concern. Optimization of ejector in the previous work is mainly focusing on the suction chamber and mixing chamber; this usually costs a lot of effort and time as there are too many dimensions. In this work, a quick method which only alters the nozzle shape is proposed to efficiently achieve the goal of optimization. Figure 11 shows the initial nozzle and the newly designed nozzle. The new one has a straight shape and its diameter is the same as the throat diameter of the initial curved shape. The CFD simulation of the new design has been conducted with the same mesh size, bubble size, and boundary conditions as depicted in Section 3.3.
Shipping ballast water treatment is a critical process to minimize the impact of ballast water discharge on the marine environment. The paper has presented a novel ballast water treatment system with a liquid-gas two-phase ejector. Numerical simulation and experimental tests are conducted to understand the performance of the ejector. Pressures of the ejector were first examined on an experimental bench to validate CFD models with different turbulence models, followed by extensive CFD analysis. Test results on the liquid-gas ejector have clearly shown that RNG turbulence model with the very fine grid size is most effective striking a balance between accuracy and computational costs. CFD analysis also indicates that the initial liquid-gas ejector may lose its absorption capability when the back pressure exceeds 2.8 bars in the ballast water treatment system. With the straight nozzle altered, the new design can efficiently improve the ejector performance at high back pressures and will not lose the absorption capability until 3.13 bar back pressure. In the further work, in-depth study on the ejector nozzle and other geometrical parameters will be carried out to find the optimal geometry for the ballast water treatment. The multiphase reaction flow will also be taken into account for understanding the mixing characteristics and the treat efficiency of ballast water.
TransCalc is a network-based computational simulation software package for the design of vacuum systems. TransCalc is based upon duct-flow prediction techniques which provide a solution across all pressure ranges (including turbulent, compressable and transitional flow). Compared to steady-state models, TransCalc uses fewer primary assumptions about the system, calculates pipe flows based on whole-system throughput and, furthermore, modifies pressures by conserving throughput over a short time interval.
At start-up, the inlet temperature, T1 may be lower than the inlet temperature expected at the full running load, causing a higher heat demand. If the warm-up time is important to the process, the heat exchanger needs to be sized to provide this increased heat demand. However, warm-up loads are usually ignored in flow type design calculations, as start-ups are usually infrequent, and the time it takes to reach design conditions is not too important. The heat exchanger heating surface is therefore usually sized on the running load conditions.In flow type applications, heat losses from the system tend to be considerably less than the heating requirement, and are usually ignored. However, if heat losses are large, the mean heat loss (mainly from distribution pipework) should be included when calculating the heating surface area.
The goal of this study is to examine the energetic and exergetic analysis of parabolic trough collector (PTSC) based integrated organic Rankine cycle (ORC) and ejector refrigeration cycle for generate power, refrigeration, and hot water. EES software program is used to carry out the performance evaluation of the trigeneration system. The first and second laws of thermodynamics are used in the calculations. According to the results of the thermodynamic analysis, the energetic and exergetic efficiency of the trigeneration system are computed as 26.67% and 14.21%, respectively. At the same time, parametric studies have been performed to examine the effect of solar radiation, temperature of turbine inlet, and generator temperature on combined cycle performance. When the parametric studies of the trigeneration system are examined, the energetic and exergetic efficiency of the trigeneration system and the total exergy destruction rise with the increase of solar irradiation and turbine inlet temperature, while the total exergetic efficiency reduces as the generator temperature rises. Moreover, the highest rate of irreversibility has the PTSC with 150 kW, while the lowest amount of irreversibility is calculated as 0.02 kW in pump of the ejector cooling system.
Description of Methodology and Computational Scheme of the ModelSetup. The present work, which is concerned with the analysis of beyonddesign-basis accidents, is actually the first full-scale hydrodynamicmodeling of a research reactor and includes almost all basic objects of thesetup. The method of [4] was used to create an input data block for theimproved evaluation code ATHLET, making it possible to describe with maximumaccuracy the geometric characteristics and hydrodynamic interconnections ofindividual objects. The modeling with the degree of detail required forconcrete calculations includes not only the reactor but also the first andsecond loops with the control system of the entire setup [5]. The crux of themethod and the basic macro objects of the reactor pool are described in [1].The initial scheme of the IR-8 equipment on which the computational model isbased is presented in Figs. 1 and 2. Figure 3 shows a three-dimensionalrepresentation of the hydrodynamic objects of the fuel assemblies for thepreparation of the data for the ATHLET code. 2ff7e9595c
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