Name: a rapid method for modeling a variable cycle engine
Uploaded: 2019-08-13T13:00:00.000+00:00
Duration: 4 min 58 s
Description: Watch this Scientific Journal Video about A Rapid Method for Modeling a Variable Cycle Engine at JoVE.com

This research was funded by the Fundamental Research Funds for the Central Universities, grant number [No. NS2018017].

1. Preparation before modeling
<ol>
	<li>Obtain design point performance.
	<ol>
		<li>Open Gasturb 13. Select Variable Cycle Engine.</li>
		<li>Click on Basic Thermodynamics. Select Cycle Design. Open DemoVarCyc.CVC.</li>
		<li>Obtain the engine design point performance. These are shown on the right side of the window.</li>
	</ol>
	</li>
	<li>Obtain component maps.
	<ol>
		<li>Open Gasturb 13. Select Variable Cycle Engine.</li>
		<li>Click on Off Design. Select Standard Maps. Open DemoVarCyc.CVC.</li>
		<li>Click on Off Design Point. Then select LPC, IPC, HPC, HPT and LPT; thus, all components maps are obtained.</li>
	</ol>
	</li>
</ol>
2. Model each component of the VCE20,21,22
<ol>
	<li>Model a single component of a VCE. Take the high-pressure compressor as an example.
	<ol>
		<li>Open Matlab. Click on Simulink. Double click on Blank Model.</li>
		<li>Click on Library, and place function to model.</li>
		<li>Double click on Function. According to the working principle of the compressor, the thermodynamic equation of the compressor is described. Then describe the equation with the MATLAB function.</li>
		<li>After finishing the MATLAB function, obtain the input and output of the compressor.</li>
		<li>Use Subsystem to mask the module. Then rename it with &#8220;compressor&#8221;. Thus far, a subsystem module called &#8220;compressor&#8221; is established.</li>
	</ol>
	</li>
	<li>Use the same steps to get the subsystems of all components including inlet, fan, duct, core driven fan stage(CDFS), bypass mixer, compressor, burner, high-pressure turbine, low-pressure turbine, mixer, afterburner and nozzle.
	<ol>
		<li>Combine output of each component with input of the next component.</li>
	</ol>
	</li>
</ol>
3. Solution of the whole model
<ol>
	<li>Construct dynamic co-working equations of whole model.
	<ol>
		<li>Construct dynamic co-working equations. Construct the following 6 independent co-working equations.</li>
		<li>Determine the flow balance equation for inlet and outlet of burner: <img alt="Equation 1" src="/files/ftp_upload/59151/59151equ01.jpg" /> 
		Wa3: compressor outlet section air flow, Wf: burner fuel flow, Wg44: high-pressure turbine inlet gas flow.</li>
		<li>Determine the flow balance equation for inlet and outlet of low-pressure turbine:<img alt="Equation 2" src="/files/ftp_upload/59151/59151equ02.jpg" /> 
		Wg44: low-pressure turbine inlet section gas flow, Wg5: low-pressure turbine outlet gas flow.</li>
		<li>Determine the flow balance equation for inlet and outlet of nozzle: <img alt="Equation 3" src="/files/ftp_upload/59151/59151equ03.jpg" /> 
		Wg7: nozzle inlet gas flow, Wg9: nozzle outlet gas flow.</li>
		<li>Determine the static pressure balance equation for inlet of rear mixer: <img alt="Equation 4" src="/files/ftp_upload/59151/59151equ04.jpg" /> 
		Ps163: static pressure of main outer bypass outlet, Ps63: static pressure of inner bypass outlet.</li>
		<li>Determine the flow balance equation of fan inlet and outlet: <img alt="Equation 5" src="/files/ftp_upload/59151/59151equ05.jpg" /> 
		Wa2: fan inlet air flow, Wa21: CDFS inlet air flow, Wa13: sub-outer bypass inlet air flow</li>
		<li>Determine the flow balance equation of CDFS outlet: <img alt="Equation 6" src="/files/ftp_upload/59151/59151equ06.jpg" /> 
		Wa21: CDFS inlet air flow, Wa125: CDFS bypass inlet air flow, Wa25: compressor inlet air flow.</li>
		<li>The above 6 independent equations constitute the following equations. 
		<img alt="Equation 7" src="/files/ftp_upload/59151/59151equ07v2.jpg" /></li>
	</ol>
	</li>
	<li>Use the N-R iteration solver in TMATS to solve the above equations.
	<ol>
		<li>Before using the solver to solve the co-working equations, set the N-R iteration solver. According to the modeling process, select the following 6 initial guesses: component map auxiliaries line of fan, CDFS, high-pressure compressor, high-pressure turbine and low-pressure turbine &#946;1, &#946;2, &#946;3, &#946;4, &#946;5, sub-outer bypass inlet flow.</li>
	</ol>
	</li>
</ol>

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We have nothing to disclose.

Based on a graphical simulation environment, a VCE component-level model can be built rapidly through modular hierarchical architecture and object-oriented modeling technology. It offers a friendly interface to users and it is convenient to analyze and design the model19.
The main limitation of this method is the execution efficiency of the model. Because the model is written in scripting language, the model needs to be recompiled every time it runs. Thus, the execution efficiency is not as good as the system language. In view of this limitation, the next key research point is how to improve the execution efficiency of the model. Another limitation is that the initial value of the N-R iteration should be considered strictly in the model, because the N-R iteration is convergent only in a small range of deviations.
A critical step in the protocol is how to obtain the component maps accurately and use the appropriate algorithm to interpolate. Whether in Gasturb or another existing engine test data, accurate component maps are helpful to build model more accurately.
In the graphical object-oriented modeling of aeroengine, whether it is the whole engine model object, the component model object or the parameter model object of each component, it is built as an independent and encapsulable module. The connection among all component modules constitute the main part of the model framework. The internal model design of each component module is for the purpose of generality, highlighting the features of easy modification and visualization of the component model. The method presented in this paper can be used not only for VCE but also for other gas turbines23.

Modern aircraft demands bring great challenges to the propulsion system, which need more intelligent, more efficient or even more versatile aircraft engines1. Future military propulsion systems also require both higher thrust at high speed and lower specific fuel consumption at low speed1,2,3,4. In order to meet the technical requirements of future flight missions, General Electric (GE) put forward the variable cycle engine (VCE) concept in 19555. A VCE is an aircraft engine that can perform different thermodynamic cycles by changing the geometry size or position of some components6. The Lockheed SR-71 "Blackbird" powered by a J58 turboramjet VCE has held the world record for the fastest air-breathing manned aircraft since 19767. It also proved many potential advantages of supersonic flight. In the past 50 years, GE has improved and invented several other VCEs, including a double bypass VCE8, a controlled pressure ratio engine9 and an adaptive cycle engine10. These studies involved not only the general structure and performance verification, but also the control system of the engine11. These studies have proven that the VCE can work like a high bypass ratio turbofan at subsonic flight and like a low bypass ratio turbofan, even like a turbojet at supersonic flight. Thus, the VCE can realize performance matching under different flight conditions.
When developing a VCE, a large amount of necessary verification works will be carried out. It may cost a large amount of time and outlay if all these works are performed in a physical way12. Computer simulation technology, which has already been adopted in developing a new engine, can not only reduce the cost greatly, but also avoid the potential risks13,14. Based on computer simulation technology, the development cycle of an engine will be reduced to nearly half, and the number of equipment required will be reduced dramatically15. On the other hand, simulation also plays an important role in the analysis of the engine behavior and control law development. For simulating the static design and off-design performance of engines, a program called GENENG16 was developed by the NASA Lewis Research Center in 1972. Then the research center developed DYNGEN17 derived from GENENG, and DYNGEN could simulate the transient performance of a turbojet and the turbofan engines. In 1989, NASA put forward a project, called Numerical Propulsion System Simulation (NPSS), and it encouraged researchers to construct a modular and flexible engine simulation program through the use of object-oriented programming. In 1993, John A. Reed developed the Turbofan Engine Simulation System (TESS) based on the Application Visualization System (AVS) platform through object-oriented programing18.
Meanwhile, rapid modeling based on graphical programming environment is being used gradually in simulation. The Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) package developed by NASA is based on Matlab/Simulink platform. It is open source and allows users to customize built-in component libraries. T-MATS offers a friendly interface to users and it is convenient to analyze and design the built-in JT9D model19.
In this article, the dynamic model of a type of VCE has been developed here using Simulink software. The modeling object of this protocol is a double bypass VCE. Its schematic layout is shown in Figure 1. The engine can work in both single and double bypass modes. When the Mode Select Valve (MSV) is open, the engine performs better at subsonic conditions with a relatively large bypass ratio. When the Mode Select Valve is closed, the VCE has a small bypass ratio and a better supersonic mission adaptability. To further quantize performance of the engine, a double bypass VCE model is built based on component-level modeling method.

<table><tbody><tr><td>Gasturb</td><td>GasTurb GmbH</td><td>Gasturb 13</td><td></td></tr><tr><td>MATLAB</td><td>MathWorks</td><td>R2017b</td><td></td></tr><tr><td>TMATS</td><td>NASA</td><td>1.2.0</td><td></td></tr></tbody></table>

a rapid method for modeling a variable cycle engine

The variable cycle engines (VCE) that combine the advantages of turbofan and turbojet engines, are widely considered to be the next generation aircraft engines. However, developing VCE requires high costs. Thus, it is essential to build a mathematical model when developing an aircraft engine, which may avoid a large number of real tests and reduce the cost dramatically. Modeling is also crucial in control law development. In this article, based on a graphical simulation environment, a rapid method for modeling a double bypass variable cycle engine using object-oriented modeling technology and modular hierarchical architecture is described. Firstly, the mathematical model of each component is built based on the thermodynamic calculation. Then, a hierarchical engine model is built via the combination of each component mathematical model and the N-R solver module. Finally, the static and dynamic simulations are carried out in the model and the simulation results prove the effectiveness of the modeling method. The VCE model built through this method has the advantages of clear structure and real-time observation.

In order to prove the validity of the simulation model, several typical performance parameters selected in static and dynamic simulations are compared with the data in Gasturb.
In a static simulation, we compare several key performance parameters of the model with these parameters in Gasturb to verify the accuracy of the static model. Table 2 shows the result of the comparison at the design point with H=0 m, Ma=0, Wf=0.79334 kg/s under a double bypass operating mode. According to the comparison, the maximum error of performance parameters between the model and Gasturb is the EPR (engine pressure ratio), which is below 2%. Table 3 shows the result of the comparison at the off-design point with H=0 m, Ma=0, Wf=0.91032 kg/s under a single bypass operating mode. Under this condition, the maximum error here is the rotational speed of low-pressure shaft, which is just below 4%. The performance parameters of both models are almost the same. Thus, the two comparison results prove that the model is accurate, and the protocol is effective at the design point.
In a dynamic simulation, with the purpose of verifying the correctness of the transition state model, we simulated two typical dynamic processes including acceleration/deceleration simulation and mode switching simulation. The acceleration/deceleration simulation are processed under a double bypass mode with H=0 m, Ma=0. Figure 2a shows the input of the fuel flow. Figure 2b, Figure 2c and Figure 2d show the response of the rotational speed, air flow and temperature before the turbine, so the model is able to perform acceleration/deceleration simulation. A mode switching simulation is carried out from the double bypass mode to the single bypass mode with H=0 m, Ma=0. As shown in the Figure 3, the VCE operating mode is switched from the single bypass mode to the double bypass mode at 5 s. In order to prevent the engine from exceeding the limited speed during the switching process, a single-variable closed-loop control is applied to the rotational speed of high-pressure shaft. Figure 3b shows that the rotational speed of high-pressure shaft is nearly unchanged during switching. Similarly, Figure 3a, Figure 3b, Figure 3c and Figure 3d show the response of the fuel flow, rotational speed, air flow and temperature before the turbine. During the two-dynamic simulation, the model can run correctly.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/59151/59151fig01.jpg" /> 
Figure 1: Schematic diagram of overall structure of variable cycle engine. 
A VCE contains a fan, a CDFS, a compressor, a burner, a turbine, a mixer, an afterburner and a nozzle. The fan and CDFS are driven by the low-pressure turbine. The compressor is driven by the high-pressure turbine. The numbers in Figure 1 represent the cross section of the engine. The definition of each cross sections is shown in Table 1. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59151/59151fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/59151/59151fig02.jpg" /> 
Figure 2. Acceleration/deceleration simulation of VCE. 
This figure presents acceleration/deceleration simulation. The fuel flow input is shown in Figure 2a. The responses of main performance parameters are shown as below. (b) The response of the high-pressure speed and the low-pressure speed. (c) The response of the air flow. (d) The response of the turbine inlet temperature. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59151/59151fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/59151/59151fig03.jpg" /> 
Figure 3. Mode switching simulation of VCE. 
This figure presents the mode switching simulation. (a) The response of the fuel flow input. (b) The response of the high-pressure speed and the low-pressure speed. (c) The response of the air flow. (d) The response of the turbine inlet temperature. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/59151/59151fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<colgroup>
	</colgroup>
	<colgroup>
	</colgroup>
	<tbody>
		<tr>
			<td>Numbe of cross section</td>
			<td>Definition</td>
		</tr>
		<tr>
			<td>2</td>
			<td>Fan inlet</td>
		</tr>
		<tr>
			<td>3</td>
			<td>Compressor outlet</td>
		</tr>
		<tr>
			<td>4</td>
			<td>Burner outlet</td>
		</tr>
		<tr>
			<td>5</td>
			<td>Low-pressure turbine outlet</td>
		</tr>
		<tr>
			<td>6</td>
			<td>Mixer inlet</td>
		</tr>
		<tr>
			<td>7</td>
			<td>Afterburner outlet</td>
		</tr>
		<tr>
			<td>8</td>
			<td>Nozzle thought</td>
		</tr>
		<tr>
			<td>9</td>
			<td>Nozzle outlet</td>
		</tr>
	</tbody>
</table>
Table 1: Definition of all cross sections. The cross-section definitions of the variable cycle engine adopted in this protocol are shown in Table 1.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<colgroup>
	</colgroup>
	<tbody>
		<tr>
			<td>Parameter</td>
			<td>Model</td>
			<td>Gasturb 13</td>
			<td>Error(%)</td>
		</tr>
		<tr>
			<td>Nl(RPM)</td>
			<td>14711</td>
			<td>14600</td>
			<td>0.76</td>
		</tr>
		<tr>
			<td>Nh(RPM)</td>
			<td>18060</td>
			<td>18000</td>
			<td>0.33</td>
		</tr>
		<tr>
			<td>T4(K)</td>
			<td>1866</td>
			<td>1850</td>
			<td>0.86</td>
		</tr>
		<tr>
			<td>FN(KN)</td>
			<td>38.18</td>
			<td>37.98</td>
			<td>0.53</td>
		</tr>
		<tr>
			<td>EPR</td>
			<td>4.1653</td>
			<td>4.2436</td>
			<td>1.85</td>
		</tr>
	</tbody>
</table>
Table 2. Comparison of the design point of the double bypass. Several key performance parameters of model are compared with those parameters in Gasturb at the design point with H=0 m, Ma=0, Wf=0.79334 kg/s.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<colgroup>
	</colgroup>
	<tbody>
		<tr>
			<td>Parameter</td>
			<td>Model</td>
			<td>Gasturb 13</td>
			<td>Error(%)</td>
		</tr>
		<tr>
			<td>Nl(RPM)</td>
			<td>15544</td>
			<td>15033</td>
			<td>3.4</td>
		</tr>
		<tr>
			<td>Nh(RPM)</td>
			<td>18123</td>
			<td>18000</td>
			<td>0.68</td>
		</tr>
		<tr>
			<td>T4(K)</td>
			<td>2036</td>
			<td>2002</td>
			<td>1.7</td>
		</tr>
		<tr>
			<td>FN(KN)</td>
			<td>41.23</td>
			<td>40.68</td>
			<td>1.35</td>
		</tr>
		<tr>
			<td>EPR</td>
			<td>4.2419</td>
			<td>4.2894</td>
			<td>1.11</td>
		</tr>
	</tbody>
</table>
Table 3. Comparison of the off-design point of the single bypass. Several key performance parameters are compared at the off-design point with H=0 m, Ma=0, Wf=0.91032 kg/s.

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A Rapid Method for Modeling a Variable Cycle Engine

Here, we present a protocol to build a component-level mathematical model for a variable cycle engine.

The variable cycle engines (VCE) that combine the advantages of turbofan and turbojet engines, are widely considered to be the next generation aircraft ...

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7.5K Views.  Nanjing University of Aeronautics and Astronautics. Here, we present a protocol to build a component-level mathematical model for a variable cycle engine.

Video: A Rapid Method for Modeling a Variable Cycle Engine

Combustion Characterization and Model Fuel Development for Micro-tubular Flame-assisted Fuel Cells

Combustion based power generation has been accomplished for many years through a number of heat engine systems. Recently, a move towards small scale power generation and micro combustion as well as development in fuel cell research has created new means of power generation that combine solid oxide fuel cells with open flames and combustion exhaust. Instead of relying upon the heat of combustion, these solid oxide fuel cell systems rely on reforming of the fuel via combustion to generate syngas for electrochemical power generation. Procedures were developed to assess the combustion by-products under a wide range of conditions. While theoretical and computational procedures have been developed for assessing fuel-rich combustion exhaust in these applications, experimental techniques have also emerged. The experimental procedures often rely upon a gas chromatograph or mass spectrometer analysis of the flame and exhaust to assess the combustion process as a fuel reformer and means of heat generation. The experimental techniques developed in these areas have been applied anew for the development of the micro-tubular flame-assisted fuel cell. The protocol discussed in this work builds on past techniques to specify a procedure for characterizing fuel-rich combustion exhaust and developing a model fuel-rich combustion exhaust for use in flame-assisted fuel cell testing. The development of the procedure and its applications and limitations are discussed.

A protocol for creating a model fuel-rich combustion exhaust is developed through combustion characterization and is applied for micro-tubular flame-assisted fuel cell testing and research.

Combustion based power generation has been accomplished for many years through a number of heat engine systems. Recently, a move towards small scale power ...

Improving the Combustion Performance of a Hybrid Rocket Engine using a Novel Fuel Grain with a Nested Helical Structure

A technique to improve the combustion performance of a hybrid rocket engine using a novel fuel grain structure is presented. This technique utilizes the different regression rates of acrylonitrile butadiene styrene and paraffin-based fuels, which increase the exchanges of both matter and energy by swirl flow and recirculation zones formed at the grooves between the adjacent vanes. The centrifugal casting technique is used to cast the paraffin-based fuel into an acrylonitrile butadiene styrene substrate made by three-dimensional printing. Using oxygen as the oxidizer, a series of tests were conducted to investigate the combustion performance of the novel fuel grain. In comparison to paraffin-based fuel grains, the fuel grain with a nested helical structure, which can be maintained throughout the combustion process, showed significant improvement in the regression rate and great potential in improvement of combustion efficiency.

A technique utilizing a solid fuel grain with a novel nested helical structure to improve the combustion performance of a hybrid rocket engine is presented.

A technique to improve the combustion performance of a hybrid rocket engine using a novel fuel grain structure is presented. This technique utilizes the ...

Modeling and Experimental Analysis of the Single-Shaft Coaxial Motor-Pump Assembly in Electrohydrostatic Actuators

An electrohydrostatic actuator (EHA) can be the most promising alternative compared with the traditional hydraulic servo actuators for its high power density, ease of maintenance, and reliability. As the core power unit that determines the performance and service life of the EHA, the motor-pump assembly should simultaneously possess a wide speed/pressure range and a high dynamic response.
This paper presents a method to test the performance of the motor-pump assembly through simulation and experimentation. The flow output characteristics were defined through simulation and analysis of the assembly at the beginning of the experiment, leading to the conclusion of whether the pump could meet the requirements of the EHA. A series of performance tests were conducted on the motor-pump assembly via a pump test bench in the speed range of 1,450-9,000 rpm and the pressure range of 1-30 MPa.
We tested the overall efficiency of the motor-pump assembly under various working conditions after confirming the consistency between the test results of the flow output characteristics with the simulation results. The results showed that the assembly has higher overall efficiency when working at 4,500-7,000 rpm under the pressure of 10-25 MPa and at 2,000-2,500 rpm under 5-15 MPa. Overall, this method can be utilized for determining in advance whether the motor-pump assembly meets the requirements of EHA. Moreover, this paper proposes a rapid test method of the motor-pump assembly in various working conditions, which could assist in predicting EHA performance.

We built a simulation model to evaluate pump flow characteristics and performance of the single-shaft coaxial motor-pump assembly in electrohydrostatic actuators and investigate the overall efficiency in a wide set of working conditions of the motor-pump assembly experimentally.

An electrohydrostatic actuator (EHA) can be the most promising alternative compared with the traditional hydraulic servo actuators for its high power ...

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Electro-hydrostatic actuators (EHAs) have been considerably researched in academia, and their applications in various industrial fields are expanding. The variable-speed EHA has now taken priority over the variable-displacement EHA, but its driving motor and associated electronics encounter issues when applied in high-power applications: low-dynamics, high thermal dissipation, high price, etc. Therefore, a variable-displacement EHA equipped with an electro-variable displacement pump (EVDP) has been considered. The EVDP itself is a mechatronic system that integrates a piston pump, a ball screw, a gearbox, and a permanent magnet synchronous motor (PMSM). Consequently, the EVDP needs to be investigated to ensure its system-level performance when applied in an EHA. In addition to the previous research on the technical parameters of the EVDP, a dedicated design method is necessary for further reducing the cost of using the EVDP and exploring its performance potential. Here, a simulation based EVDP preliminary design method is selected for designing a 37 kW EVDP. Firstly, a previously proposed multidisciplinary model of the EVDP is extended by improving the parameter generation, including the EVDP life, reliability, control models, etc. Secondly, the proposed model is partially verified using a downsized prototype. Thirdly, the EVDP is simulated at a system level, supported by the proposed model. The EVDP performance is evaluated according to the specified design requirements. The temperature, bandwidth and accuracy, reliability and lifetime, etc., are all predicted for the EVDP. The simulation results demonstrate the EVDP's applicability in variable-displacement EHA. The proposed modeling and simulation method can be used to evaluate diverse EVDP performance and respond to general design requirements. The method can also support the resolution of the preliminary design challenges in terms of limited information and robustness. Therefore, the proposed method is appropriate for the realization of the simulation-based EVDP preliminary design method.

A simulation model specifically supporting the preliminary design of an electro-variable displacement pump (EVDP) is developed and partially verified by experiments. The control performance, life, reliability, etc., can all be evaluated using the proposed model, which covers the main performance requirements under the EVDP preliminary design task.

Electro-hydrostatic actuators (EHAs) have been considerably researched in academia, and their applications in various industrial fields are expanding. The ...

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

The electro-hydrostatic actuator (EHA) is a promising actuating apparatus used in flight control systems for more electric aircraft (MEA) due to its high power density and low maintenance. Since the reliability of the system decreases with increasing complexity, fault detection is becoming increasingly important. In this paper, an adaptive filter was designed based on a normalized least mean square (NLMS) algorithm, which could identify the resistance of the motor windings online to detect electrical faults in the EHA. Additionally, based on the analytical relationship between rotational speed and displacement, a rotational speed estimation method was designed. By comparing the actual rotational speed with the estimated one, hydraulic faults could be detected. To verify the efficacy of the aforementioned method, software was applied for the modeling and simulations, which included fault injection and detection. On this basis, an experimental platform was built and then subjected to a series of validation experiments. The results indicate that the fault detection method has the potential to detect electrical and hydraulic faults in an EHA.

In this paper, an adaptive filter based on a normalized least mean square (NLMS) algorithm and a rotational speed estimation method are introduced to detect the electrical and hydraulic faults of the electro-hydrostatic actuator (EHA). The efficacy and feasibility of the aforementioned methods are verified through simulations and experiments.

The electro-hydrostatic actuator (EHA) is a promising actuating apparatus used in flight control systems for more electric aircraft (MEA) due to its high ...

Finite Element Modeling for the Simulation of the Quasi-Static Compression of Corrugated Tapered Tubes

In this study, the quasi-static compression performance of tapered tubes was investigated using finite element simulations. Previous studies have shown that a thickness gradient can reduce the initial peak force and that lateral corrugation can increase the energy absorption performance. Therefore, two kinds of lateral corrugated tapered tubes with variable thicknesses were designed, and their deformation patterns, load displacement curves, and energy absorption performance were analyzed. The results showed that when the thickness variation factor (k) was 0.9, 1.2, and 1.5, the deformation mode of the single corrugated tapered tube (ST) changed from transverse expansion and contraction to axial progressive folding. In addition, the thickness gradient design improved the energy absorption performance of the ST. The energy absorption (EA) and specific energy absorption (SEA) of the model with k = 1.5 increased by 53.6% and 52.4%, respectively, compared with the ST model with k = 0. The EA and SEA of the double corrugated tapered tube (DT) increased by 373% and 95.7%, respectively, compared with the conical tube. The increase in the k value resulted in a significant decrease in the peak crushing force of the tubes and an increase in the crushing force efficiency.

This protocol describes the study of the quasi-static compression performance of corrugated tapered tubes using finite element simulations. The influence of the thickness gradient on the compression performance was investigated. The results show that proper thickness gradient design can change the deformation mode and significantly improve the energy absorption performance of the tubes.

In this study, the quasi-static compression performance of tapered tubes was investigated using finite element simulations. Previous studies have shown ...

Design and Optimization Strategies of a High-Performance Vented Box

This study aims to solve the problems of air flow chaos and poor performance in a vented box caused by the heterogeneous distribution of airflow through the design of the internal structure of the vented box with constant energy consumption. The final goal is to evenly distribute the airflow inside the vented box. Sensitivity analysis was performed for three structural parameters: the number of pipes, the number of holes in the middle pipe, and the number of each increment from the inside to the outside pipe. A total of 16 random array sets of three structural parameters with four levels were determined using the orthogonal experimental design. Commercial software was used for the construction of a 3D model for the selected experimental points, and this data was used to obtain the airflow velocities, which were then used to obtain the standard deviation of each experimental point. According to the range analysis, the combination of the three structural parameters was optimized. In other words, an efficient and economical optimization method considering the performance of the vented box was established, and it could be widely used to extend the storage time of fresh food.

Here, we present the range analysis method to optimize the sample points generated by an orthogonal experimental design to ensure that fresh food can be stored in a vented box for a long time by regulating the airflow pattern.

This study aims to solve the problems of air flow chaos and poor performance in a vented box caused by the heterogeneous distribution of airflow through ...

Surrogate Model Development for Digital Experiments in Welding

The manufacturing industry heavily relies on welding processes to join materials, forming integral components across various sectors. Many aspects will influence the quality of the weld and finally affect the structure integrity of the weldment. Welding-induced residual stress, a consequence of the thermal cycling inherent in these processes, significantly impacts the structural integrity and performance of fabricated components. Understanding and predicting this residual stress is crucial for enhancing the reliability and durability of welded structures. However, quickly assessing a welding setup in digital experiments presents significant challenges, as a traditional simulation may be time-consuming. This research outlines the application of a workflow to construct an artificial neural network-based surrogate model to predict welding-induced residual stress. The model is built using data automatically generated from finite element simulations through Python scripts based on macro functions. Unlike traditional methods that rely on manual preprocessing and finite element simulations, this approach significantly reduces the time and effort required for simulation setup and data extraction, enhancing overall efficiency. By ensuring that all simulation steps are performed consistently through macro functions, the method eliminates human-induced variability, leading to improved reproducibility. Furthermore, the automation of data generation makes it possible to create extensive datasets necessary for training machine learning models, overcoming the limitations of labor-intensive traditional techniques. The workflow contains four main steps: build a standard weld finite element simulation and validate the finite element simulation results against experimental data; develop scripts for large dataset generation using a macro function that records the preprocessing and postprocessing steps of the finite element simulation; use the scripts to generate the required data; develop surrogate models and test their performance. The artificial neural network demonstrated high accuracy in predicting stress levels, closely aligning with simulation results on the test dataset and a relative root mean square error of 0.0024.

This protocol outlines a general workflow for constructing an artificial neural network for welding simulation using datasets generated automatically through Python scripts with macro functions. The workflow is validated against a benchmark case involving single-pass, straight-line welding. The surrogate model's predictive accuracy shows a strong agreement with finite element simulations.

The manufacturing industry heavily relies on welding processes to join materials, forming integral components across various sectors. Many aspects will ...

Propulsion and Thrust

Source: Alexander S Rattner; Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA
Aircraft, rockets, and ships produce propulsion by accelerating surrounding fluid or high temperature combustion products to high velocity. Because of the principle of conservation of momentum, the increased fluid velocity results in an effective thrust force on the vehicle. The thrust capabilities of propulsion systems are often measured with static thrust tests. In these tests, propulsion systems are mounted and operated on fixed, instrumented platforms, and the holding force on the mounts is measured as the thrust
In this experiment, a small-scale static thrust measurement facility will be constructed and modeled. The thrust curves for two model aircraft motors and propeller systems and a computer cooling fan will be measured. Thrust efficiencies will also be evaluated (thrust force / electrical power input). Measured thrust values will be compared with theoretical predictions based on measured air velocities.

Aircraft/Rocket/Ship Propulsion; Static Thrust Measurement

Source: Alexander S Rattner; Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, PA
Aircraft, rockets, ...

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Internal Combustion Engine

The internal combustion engine is a heat engine that uses the byproducts of combustion as the working fluid instead of using a heat transfer medium to transfer heat. The combustion is done in a way that produces high-pressure combustion products that can be expanded through a turbine or piston to create work. Internal combustion engines can again be categorized into three kinds: (1) spark ignition gasoline engines, most commonly used in automobiles, (2) compression ignition diesel engines that are used in heavy vehicles and industrial machinery, and (3) gas turbines, which are used in aircraft.
The working of the internal combustion engine can be explained using spark ignition gasoline engines. Most of these are four-stroke cycle engines requiring four piston strokes to complete a cycle. The four strokes are the intake stroke, the compression stroke, the ignition and power stroke, and the exhaust stroke.
During the intake stroke, the intake valve is open, and the exhaust valve is closed. The descending piston draws the air-fuel mixture through the intake valve. At the end of this stroke, the intake valve is closed, and the piston compresses the mixture approximately adiabatically. This stroke is called the compression stroke. In the power stroke, the spark plug ignites the gas. The heated gas expands almost adiabatically to its maximum volume. Work is done on the piston by pushing it down. Finally, the exhaust valve opens, and the piston moves up, expelling the burned gas from the cylinder and preparing the cylinder for the next intake stroke.
The efficiency of a combustion engine is expressed in terms of the compression ratio. It is the ratio of the maximum to the minimum volume of the cylinder. For automobile engines, it ranges from 8 to 10.

Silnik spalinowy

The internal combustion engine is a heat engine that uses the byproducts of combustion as the working fluid instead of using a heat transfer medium to ...