Thrust Power Research Articles

Analysis of the Effects of Ionic Liquid Properties on Electrospray Thruster Performance.

Ionic liquids (ILs) have proven extremely useful for a wide variety of roles, including as propellants for electrospray thrusters (ETs), due to their unique physical and chemical properties, as well as the potential tunability of those properties, through chemical engineering. However, there is a lack of literature exploring the effects of IL properties on ET operation. This paper presents experimental results investigating key physical properties of the common ILs 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (EMI-TFSI), 1-butyl-3-methylimidazolium trifluoromethanesulfonate (BMI-TFO), EAN, and Bmpyr-DCA not provided by manufacturers or reported in the literature, namely, their electrochemical stability windows (ESWs) and contact angles. Cyclic voltammetry experiments were employed to define the ESW of each IL, which is necessary for long-term ET operation while avoiding chemical breakdown. Contact-angle measurements were also conducted to study the wettability of the ILs on glass surfaces to be used for ET thruster substrates [Howell, J. H.; . J. Electrost. 2023, 122, 103799]. In addition, an analytical discussion is presented using established parametric relationships and scaling laws to examine the effects of relevant IL physical properties, such as surface tension and ion molecular weights, on ET performance. The results demonstrate the relative impact of IL properties on important ET figures of merit such as thrust density, power density, and specific impulse, which provide key insights into the future development of novel ILs specifically tailored for use as ET propellants.

Rotor noise in non-axial inflow conditions

This paper presents an experimental study on characterising the aerodynamic and far-field acoustic performance of rotors operating in non-axial inflow conditions. The current experiments were carried out with a two-bladed rotor, operating with a tip Mach number of 0.56, approaching the practical tip Mach numbers expected of urban air mobility vehicles. Synchronous measurements of the aerodynamic force, far-field acoustics and blade phase angle were undertaken to provide insights on both the time-averaged and phase-averaged correlation between the rotor aerodynamic loading and the emitted noise. The far-field acoustic spectra are compared across a range of advance ratios (0.01≤μ≤0.04) and forward tilting angles (0°≤α≤30°). When the inflow velocity increases, both the tonal and broadband components increase. Moreover, higher harmonics of the blade passing frequency are observed to become more prominent at higher advance ratios. As the rotor tilts forward from edgewise flight conditions, the broadband noise component reduces significantly, with the tones at fundamental blade passing frequency and higher harmonics also reducing in magnitude, agreeing well with the steady and unsteady thrust coefficients measured. From the aerodynamic loading, acoustic spectra and the directivity results, a transition from near-edgewise to near-axial modes of operation can be discerned at a tilt angle of approximately 16°. More interestingly, the phase-averaged thrust and acoustic power results show notable variations of the blade loading and acoustic emission through one full rotor rotation. At higher advance ratios and shallow tilting angles, the phase location of peaks in the root-mean-square of the fluctuating thrust coefficient agrees very well with those from the acoustic power, suggesting a strong correlation between the flow unsteadiness and the noise at these non-axial conditions, contributing to higher overall sound pressure levels.

Free-surface-induced ground effect for flapping swimmers

Numerous flying and swimming creatures use the ground effect to boost their propulsive performance, with the ‘ground’ referring to either a solid boundary or a free surface. While our knowledge of how a solid boundary affects biolocomotion is relatively comprehensive, the ground effect of a free surface is not fully understood. To address this limitation, we conduct a numerical investigation on the propulsion performance of a flapping plate under a free surface, subject to a range of control parameters. When the Froude number ( $Fr$ ) is very low (i.e. little surface deformation), the effects of a free surface are similar to those of a solid boundary, with enhanced thrust and input power but little change in efficiency. However, as $Fr$ increases (i.e. more surface deformation), our results reveal an optimal $Fr$ of approximately 0.6, where the free surface induces a more streamlined flow around the flapping plate, effectively reducing the added mass. This results in a significant decrease in input power and greatly enhanced efficiency.

Numerical simulation investigation on aerodynamic characteristics of rotor in plateau environment

To investigate the impact of high-altitude environments on helicopter rotor aerodynamic characteristics, this study developed a computational model that integrates CFD, BP neural networks, and the free wake method. The accuracy of the model was validated through wind tunnel experiments and comparisons with CFD results. Using this model, the effects of altitude and temperature at high altitudes on rotor aerodynamic characteristics during hover and forward flight were studied. The results indicate that with constant temperature, rotor thrust significantly decreases as altitude increases, primarily due to reduced air density. As altitude rises with unchanged temperature, the decrease in air density directly affects the lift and thrust generated by the rotor, leading to a decline in hover performance. Furthermore, the study found that rotor aerodynamic coefficients do not vary significantly across different altitudes. Further analysis suggests this stability is due to the high Reynolds number in the calculated state. In the high Reynolds number range, changes in Reynolds number have minimal impact on aerodynamic coefficients, resulting in relatively stable aerodynamic performance across varying altitudes. At a constant altitude, lower temperatures lead to slight increases in rotor thrust and torque, while the thrust coefficient and power coefficient remain almost unaffected. This phenomenon is attributed to changes in air density and viscosity caused by the lower temperatures. The increase in air density positively impacts thrust and torque, while the reduction in air viscosity decreases the rotor's surface frictional resistance. This partially offsets the increase in lift and drag caused by the higher air density, leading to negligible changes in thrust and power coefficients.

A novel multi-objective optimization scheme of electric turbo compressor system in hydrogen fuel cell for reducing energy consumption and axial thrust

Electric turbo compressor (ETC) can recover the exhaust energy and reduce the motor power consumption, which is the future development of the air management system for fuel cell. However, the large imbalances of axial thrust and energy between the compressor and turbine leads to low reliability and efficiency of ETC. In this study, a multi-objective optimization scheme was proposed to explore the lowest ETC axial thrust and electric power consumption. First, the coupled model including compressor, turbine and axial thrust sub-models were established in MATLAB. To verify the model, computational fluid dynamics(CFD) model were established in ANSYS CFX and experimental tests were carried out. The electric power differences between the MATLAB model and experiment is within 4.36 % and the axial thrust deviations between the MATLAB and CFD model is within 5.46 %.Then, eight geometric parameters of compressor and turbine rotors are selected as independent optimization variables. NSGA-ΙΙ multi-objective optimization algorithm was adopted to search for low axial thrust and power consumption solutions. Finally, the optimization results show that the efficiency of the compressor and turbine is increased by 6.39 % and 2.75 % at design point, respectively. The electric power consumed by the motor is reduced by 7.80 % and the axial thrust of the ETC is reduced by 18.83 %.

Analytical model of a Hall thruster

Hall thrusters are one of the most successful and prevalent electric propulsion systems for spacecraft in use today. However, they are also complex devices and their unique E×B configuration makes modeling of the underlying plasma discharge challenging. In this work, a steady-state model of a Hall thruster is developed and a complete analytical solution presented that is shown to be in reasonable agreement with experimental measurements. A characterization of the discharge shows that the peak plasma density and ionization rate nearly coincide and both occur upstream of the peak electric field. The peak locations also shift as the thruster operating conditions are varied. Three key similarity parameters emerge that govern the plasma discharge and which are connected via a thruster current–voltage relation: a normalized discharge current, a normalized discharge voltage, and an amalgamated parameter, α¯, that contains all system geometric and magnetic field information. For a given normalized discharge voltage, the similarity parameter α¯ must lie within a certain range to enable high thruster performance. When applied to a krypton thruster, the model shows that both the propellant mass flow rate and the magnetic field strength must be simultaneously adjusted to achieve similar efficiency to a xenon thruster (for the same thruster geometry, discharge voltage, and power level).

Physics-guided federated learning as an enabler for digital twins

Digital twins bring the potential to increase the efficiency of assets, systems, and processes by building virtual replicas through real-time data and modeling. However, data are often confidential and distributed, high-fidelity models based on physical principles tend to be slow and require detailed knowledge about the asset design that may not be available, simplified models lack accuracy, and data-driven models are not interpretable and limited to their training space. We demonstrate the interplay of two enabling technologies, namely federated learning and hybrid analysis and modeling, to combine the strengths of physics-based and data-driven models on distributed data sets that are kept confidential by different stakeholders. Throughout the work, an ensemble of physics-guided neural networks is designed, optimized, and validated to infer the parameters of digital twin components. The physics-guided neural network is injected with output from a simplified physics-based model in intermediate layers for increased performance, and the injection layer is optimized through weight regularization. The model is then integrated into a simulation of the digital twin asset and validated there. It is shown that the model outperforms the simplified physics-based and the data-driven models both on component and on asset level. In the final step, the physics-guided neural network is trained using federated methods, which allows training on confidential data owned by different stakeholders without requiring the stakeholders to share their data. We show that federated hybrid models can – with the right training strategy – by design achieve results that are always identical and potentially superior to models trained on a central data set. The problem chosen for this demonstration is the prediction of airfoil lift and drag coefficients based on the airfoil shape and the angle of attack, which is a task crucial for simulating wind turbines. Using the physics-guided neural network, the estimation of the airfoil coefficients experiences a speedup of several orders of magnitude compared to the high-fidelity simulation, and integration into blade element momentum theory shows that the turbine thrust, torque, and mechanical power can be accurately calculated. The federated approach makes it possible to extend the training of the model to any number of distributed confidential data sets from both simulations and experiments to further increase the model’s accuracy.

Armature Reaction Analysis and Suppression of Voice Coil Actuator Based on an Improved Magnetic Equivalent Circuit Model

The high thrust density voice coil actuator (VCA) is a key component for the deployers to determine the CubeSats' separation velocity in orbit directly. To improve the VCA's thrust density and power consumption, it is essential to analyze the armature reaction under heavy current work conditions. This paper proposes a dynamic splitting method of the magnetic equivalent circuit (MEC) model for analyzing the armature reaction of the VCA. This MEC model can effectively reveal the interaction mechanism between the dynamic winding field and the permanent magnet (PM) field, which provides an approach to readily and quickly analyze the armature reaction. Based on the understanding of the mechanism, we found an effective way to suppress the armature reaction and propose a new VCA with double PM flux circuits. The electromagnetic performances of the new configuration are evaluated by comparing it with the conventional one. Both the theoretical and experimental results show that the new structure achieves lower magnetic saturation, lower armature reaction, and higher thrust density. A research prototype was constructed and experimentally tested to verify the theoretical results of the armature reaction, magnetic field, thrust, separation velocity, and other performances. The new VCA realizes a wide and accurate modulation of separation velocity for the CubeSats.

Multi-step real-time prediction of hard-rock TBM penetration rate combining temporal convolutional network and squeeze-and-excitation block

Accurate penetration rate prediction enhances rock-breaking efficiency and reduces disc cutter damage in tunnel boring machine (TBM) construction. However, this process faces significant challenges such as the high uncertainty of ground conditions and the complexity of maintaining optimal TBM operation in long and large tunnels. To address these challenges, we propose TCN-SENet++, a novel hybrid multistep real-time penetration rate prediction model that combines a temporal convolutional network (TCN) and a squeeze-and-excitation (SENet) block for aided tunneling. This study aims to demonstrate the application of TCN-SENet++, as well as other models such as RNN, LSTM, GRU, and TCN, for TBM penetration rate prediction. The model was developed using actual datasets collected from the Yin-Song diversion project. We employ a 30-s time step to predict the future time steps of the penetration rate (1st, 3rd, 5th, 7th, and 9th). The features that influence the penetration rate, such as the cutterhead torque, thrust, and cutterhead power, were considered. A comparative analysis using the mean absolute error and mean squared error revealed that the TCN-SENet++ model outperformed the other models, including RNN, LSTM, GRU, TCN, and TCN-SENet+. In comparison, TCN-SENet++ achieved average MSE reductions of 18%, 6%, 3%, 1%, and 2%, respectively. The TCN-SENet++ model demonstrated fewer errors in the new project, validating its effectiveness and suitability for real-time penetration rate prediction in TBM construction.

Fabrication, machining (dry vs. cryogenic) and life cycle analysis of hybrid titanium composite laminates (HTCL)

Titanium-based fiber metal laminates, also known as hybrid titanium composite laminates (HTCL), are new-age potential materials used in the field of supersonic and high-speed passenger aircraft due to their better corrosion resistance, higher stiffness, fatigue and impact resistance at both elevated and room temperature. However, the difficult-to-machine nature mandates using effective but sustainable coolant during machining. Therefore, in the present study, drilling of HTCL is done in a dry and cryogenic LCO2 environment, considering various responses such as thrust force, torque, surface roughness, tool wear, chip analysis, power consumption and specific cutting energy. Further, a life-cycle analysis was carried out to evaluate the impacts of these two cutting conditions. The results indicate that cryogenic cooling improved the hole surface finish (up to 25%) by reducing the torque values significantly by 25–30%. Furthermore, tool life is improved (up to 48.6%), and power consumption is reduced (up to 13.3%). These outcomes make cryogenic with LCO2 more favorable to use over dry conditions for this novel material. Nevertheless, condensing CO2 into liquid form necessitates a higher consumption of energy and natural resources. Furthermore, its direct release into the environment results in environmental impacts (up to 17–20%) compared to dry machining.

Modelling guided energy management system for a hydrogen–fuelled harbour tug

The use of hydrogen as a source of fuel for marine applications is relatively nascent. As the maritime industry pivots to the use of alternate low and zero-emission fuels to adapt to a changing regulatory landscape, hydrogen energy needs to present and substantiate a technical and commercially viable use case to secure its value proposition in the future fuel mix. This paper leverages the technoeconomic and environmental assessment previously performed on HyForce, a hydrogen-fuelled harbour tug which has shown encouraging results for both technical and commercial aspects. This study aims to create a digital twin of HyForce to accurately predict her operability in real-world scenarios. The results from this study identify the strengths and drawbacks of the proposed use case. This is achieved by embedding the detailed design of HyForce in a virtual environment to further evaluate its operational performance through Computational Fluid Dynamics (CFD) simulations of realistic environmental conditions such as wind, wave, sea currents, and friction attributed to the properties of seawater. The results from this study indicate a base case power requirement of 93 kW to 1892 kW to achieve speeds of 5 to 12 knots in the absence of external environmental influences. Consequently, the speed of HyForce has a profound impact on total resistance peaking at 97.3 kN at 12 knots. Seawater properties such as low seawater temperature of 0 °C, and a high salinity of 50 g/kg increased friction. Additionally, wind speeds of 10 m/s acting on HyForce, delivered a resistance of 3 kN. However, these will be well mitigated through the design of the propulsion system which will be able to deliver a thrust power of 1892 kW and with assistance from the energy storage systems produce 2 MW of power to overcome the resistance experienced. The findings presented in this paper can serve as a foundation for constructing a robust model for the development of a predictive controller for future work. This controller has the potential to optimize the configuration of hydrogen and battery energy storage, aligning with desired cost functions.

Decay Of Bow Thruster Induced Near-Bed Flow Velocities At A Vertical Quay Wall: A Field Measurement

During berthing operations vessels use bow thruster(s) to improve their manoeuvrability, making them less dependent on the assistance of tugboats. While manoeuvring, the transversal bow thruster jet can reflect on the quay wall and partially be directed towards the bed. At the intersection between the quay wall and the bed, the jet reflects again leading to a highly turbulent and complex flow field (Figure 1). When the bed is left unprotected scour may occur, which can eventually lead to instability of the quay wall (Roubos et al., 2014). Over the years, the shipping industry has been developing continuously, characterized primarily by the upscaling in size of inland- and sea-going vessels (OECD, 2015; Weenen et al., 2020; Looye, 2021). As a result, vessels have larger draughts, more power and larger thruster diameters leading to higher hydraulic loads on quay walls and bed protections of berthing facilities (Roubos & Verhagen, 2007). To complicate the matter even more, the jet from a transversal bow thruster is confined by the hull of the vessel, the quay wall and the bed. Leading to a complex flow field of the reflected jet and an unknown decay in near-bed flow velocities. Resulting in uncertainties in the design of bed protections, especially in the required width.

Impact of blade shape on the aerodynamic performance and turbulent jet dynamics produced by a ducted rotor

A ducted rotor system was used to produce turbulent jets with a Reynolds number up to 5.97 × 105 and Mach number of 0.222 based on mean streamwise velocity. Three rotors with a diameter of 11.8 cm were manufactured and tested inside a duct with a 1 mm tip clearance at a speed up to 30 000 revolutions per minute (rpm). All rotor blades contain the same aspect ratio of 2.2, a National Advisory Committee for Aeronautics 2410 airfoil, and ideal pitch distribution. However, three different blade planform shapes were used including a rectangular shape with constant chord, trapezoidal shape with a taper ratio of 0.5, and elliptical shape where the trailing edge of the blade is expressed with an elliptical function. The rotor thrust and electric power were measured, and the thrust coefficient and figure of merit was computed. The flow-field produced by the ducted rotors was measured in the near-field using laser Doppler velocimetry techniques. The inflow velocity approximately 3 mm upstream of the rotor blade leading edge was acquired and its significance on blade aerodynamics and performance is analyzed. Time-averaged contours of cross-stream vorticity reveal intense hub and blade tip vortex structures, which are impacted by the shape of the blade, particularly in the blade tip region. Tip vorticity as well as streamwise turbulence intensity and turbulent kinetic energy in this region were mitigated for the rotors with trapezoidal and elliptical blades. However, the turbulent structure of the jet produced by all three rotor blade shapes showed similarity at a mere 2.8 rotor diameters downstream of the rotor. This finding emphasizes the importance of blade design on the near-field dynamics of ducted rotor flows for aircraft propulsion.

Characteristic Investigation of a Novel Aircraft SOFC/GT Hybrid System under Varying Operational Parameters

In this study, the implementation of a solid oxide fuel cell–gas turbine hybrid engine for primary propulsion and electric power generation in aircraft is investigated. The following three parameters, which are crucial in attaining optimal performance at any point in the flight profile, were identified: the oxygen-to-carbon ratio of the catalytic partial oxidation reformer, the fuel utilization factor of the fuel cell, and the airflow split ratio at the outlet of the high-pressure compressor. The study assesses the impact of varying these parameters within specified ranges on the performance of the hybrid system. At the design point, the system yielded a total power output of 1.96 MW, with 102.5 kW of electric power coming from the fuel cell and 7.9 kN (1.86 MW) of thrust power coming from the gas turbine. The results indicate that varying the oxygen-to-carbon ratio affected the fuel cell’s fuel utilization and resulted in a slight decrease in gas turbine thrust. The fuel utilization factor primarily affected the power output of the fuel cell stack, with a minor impact on thrust. Notably, varying the airflow split ratio showed the most significant influence on the overall system performance. This analysis provides insights into the system’s sensitivities and contributes to the development of more sustainable aircraft energy systems.

An improved energy management strategy for hybrid electric powered aircraft based on deep reinforcement learning

Electric airplanes have attracted a great deal of attentions because of their strategic commercial values and low emissions. One of the essentials for efficient control and management of hybrid electric propulsion aircraft is a well-designed energy management strategy (EMS). A new EMS approach based on deep learning is introduced in this study to realize thrust distribution and power distribution, consequently lowering aircraft fuel consumption. A model of hybrid electric propulsion power system including turbine engines and lithium-ion battery pack is constructed to act as an application environment. An intelligent energy management strategy based on deep reinforcement learning (DRL) is then proposed in this paper. Two DRL agents based on twin delayed deep deterministic policy gradient (TD3) are combined in the hierarchical framework. The multi-agents are trained to handle the energy management problem in this paper. In a finite period of time, the training process is accomplished. After training, the simulation result of the test shows that this DRL-based EMS reduces the equivalent fuel consumption by 2.2% compared with that using the existing method, and preserves 99.9% of the battery state of health (SOH). The battery pack's state of charge (SOC) regresses precisely to the reference value at the end. Particularly, the proposed EMS is able to work properly for different flight profiles and various initial SOCs. The results of this paper provide preliminary supports for the feasibility and superiority of deep reinforcement learning applied to the energy management strategy of series hybrid electric aircraft.

A comprehensive study on the aerodynamic influence of stationary and moving obstacles on an isolated phantom DJI 3 UAV propeller

AbstractUnmanned aerial vehicle (UAV) technology is experiencing strong growth in many fields such as military and civil. When operating around obstacles and in the proximity of walls or moving objects, the UAV is constrained to thrust and power consumption variation induced by several aerodynamic effects that can lead to severe flight instability. In this paper, a methodology based on multiple reference frames (MRF) is developed and applied to computational fluid dynamics (CFD) simulations on a Phantom DJI 3 propeller to reproduce the effect of fixed and moving wall proximity on the propeller aerodynamic performances. When hovering (3000 rpm) at 0.2 m above a moving obstacle (15 m/s), the results have shown a huge decrease in the thrust by 11.3% when compared to fixed obstacle thrust. This effect, however, is reduced when the propeller is hovering at 5000 rpm and neglected at 9550 rpm. Finally, the moving obstacle had a significant impact on the propeller's aerodynamic performance, resulting in a decrease in thrust force and power consumption at low hovering rotational velocities. Especially, when the obstacle is moving at a fast speed, the UAV could properly use high rotational velocity to maintain high power loading and ensure hovering stability.

Modeling of the Flight Performance of a Plasma-Propelled Drone: Limitations and Prospects

The resurgence in interest in aircraft electro-aerodynamic (EAD) propulsion has been sparked due to recent advancements in EAD thrusters, which generate thrust by employing a plasma generated through electrical discharge. With potentially quieter propulsion that could contribute to the generation of lift or the control of attitude, it is important to determine the feasibility of an EAD-propelled airplane. First, the main propulsive characteristics (thrust generation and power consumption) of EAD thrusters were drawn from the literature and compared with existing technologies. Second, an algorithm was developed to couple standard equations of flight with EAD propulsion performance and treat the first-order interactions. It fairly replicated the performance of the only available autonomous EAD-propelled drone. A test case based on an existing commercial UAV of 10 kg equipped with current-generation EAD thrusters anticipated a flight of less than 10 min, lower than 30 m in height, and below 8 m · s −1 in velocity. Achieving over 2 h of flight at 30 m of height at 10 m · s −1 requires the current EAD thrust to be doubled without altering the power consumption. For the same flight performance as the baseline UAV, the prediction asked for a tenfold increase in the thrust at the same power consumption.

Characteristics Analysis and Comparison of a Cylindrical Linear Induction Motor with Composite Secondary Structure

The cylinder linear induction motor (CLIM) is a variation of the rotary induction motor. Its structure is simple, it has a low manufacturing cost, and it can generate linear thrust without the need for a conversion mechanism. It is particularly suitable for electromagnetic catapults, magnetic levitation transport, and industrial production fields, due to its strong environmental adaptability. Designing a high-thrust and high-efficiency CLIM is a great challenge due to its inherent drawbacks, such as the low thrust density and power density of induction motors. In this article, two CLIMs with different topologies are proposed to meet the demand for control-rod drives in high-temperature and high-pressure environments. The article elucidates the topologies of the two CLIMs and proposes an analytical computational approach for the CLIM. Modern optimization algorithms were utilized to optimize the design of the structural parameters of both CLIMs. A 3D-FEA simulation was used to compare and analyze the air-gap magnetism and thrust characteristics of two CLIMs. The results indicate that the copper-ring secondary CLIM has a higher thrust density and is more suitable for use in control-rod drive mechanism (CRDM) systems.

A review of the impact of ground test-related facility effects on gridded ion thruster operation and performance

A key consideration in the interpretation of ground test data of electric propulsion devices purposed for spaceflight is understanding how facility-effects influence thruster operation. This understanding is critical to the prediction of actual thruster performance in space. The necessity of science-based predictions gleaned from ground tests are particularly critical at higher thruster power levels. Operation of engines at higher power levels in vacuum chambers leads to considerable elevation in background pressure, background plasma density, and backsputter rates. This review examines the influence of ground test facility effects on gridded ion thruster operation. Ground test operation is compared with flight data, where available, to obtain a clear picture of operational differences. Mitigation strategies to alleviate facility effects are also commented upon.

Does Bistability Improve Swimming Performance in Robotic Fish?

A bistable mechanism has two stable states with energy input required to move from one stable state to another. This energy barrier allows for energy storage and release which can be used to improve systems characteristics. Bistability has been used to increase the frequency range over which a kinetic energy harvester is effective, and it has been proposed that bistability can increase the efficiency of biomimetic swimming robots. However, experiments involving bistable swimming robots have typically used bistability as a means of overcoming limitations inherent to soft actuators, rather than to increase overall performance. This article implements bistability into a swimming robotic and compares performance with and without bistable action. The static thrust generation and power consumption for bistable and nonbistable configurations for five different tail morphologies are compared. Bistability is generally found to increase the system efficiency, particularly at lower frequencies where increases are observed up to 250%. The untethered swimming speed of the robot in open water is also found to increase by approximately 30%. The results show that bistability can offer direct performance benefits for biomimetic swimming, but that the bistable transmission must be well tuned to the dynamics of the rest of the system.