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In this paper, an electric servo actuator implementation scheme with an energy recovery link is proposed to address the potential energy being wasted when a load falls. The new electric servo actuator recovers the potential energy dissipated during the load-falling progress by using an accumulator. The accumulator can also provide extra thrust when the load is lifted. Moreover, a dynamic model is established based on the theory of power bond graphs to analyze the dynamic and energy consumption characteristics of the new electric servo actuator. The simulation results show that the new electric servo actuator can significantly reduce the required motor power and effectively recover the potential energy of the load. This achievement is very significant for improving the energy efficiency of electric servo actuators and mitigating global warming. In addition, the modeling method used in this paper has important reference significance for the energy consumption analysis of other mechanical systems with complex energy domains. [ABSTRACT FROM AUTHOR]

The effectiveness of model-based diagnosis strongly depends on the model's authenticity and is impacted by various uncertainties. Measurement uncertainty is governed by the probability method, and parameter uncertainty can be handled by the linear fractional transformation, whereas structure uncertainty and errors are rarely considered. In this paper, an improved bond graph (BG) model is proposed, which adopts subsystems to substitute modelling errors, namely parameter uncertainty and structure uncertainty. A multi-dimensional Fibonacci optimization algorithm is developed to identify the parameters of subsystems to obtain the subsystem-based diagnostic hybrid BG (SDHBG) model. Fault diagnosis is realized by comparing the residuals and thresholds derived from the SDHBG. Experiments are conducted to validate the key concepts of the proposed methods. Subsequently, the results suggest its effectiveness. [ABSTRACT FROM AUTHOR]

The bond-graph (BG) enables to model multi-physics systems in the energy domains. This paper shows that BG models are an alternative, more intuitive and simpler to interpret, graphical tool as compared to existing dynamic models for performance prediction of the line-start permanent-magnet synchronous motors (LSPMSMs). It includes electrical, magnetic, and mechanical energy domains where the stator windings, rotor bars, and permanent magnets are the main components of the model. The dynamical equations of the proposed BG are extracted and solved using the MATLAB ordinary differential equation solver for a sample LSPMSM. The dynamics of the studied LSPMSM is investigated under two operating conditions (1) a healthy motor and (2) a motor with broken rotor bars. The simulation results are compared with the finite-element analysis (FEA) as the most accurate method to simulate the electric motor behaviour. It is shown that the proposed BG model accurately predicts the performance parameters of the motor such as current, torque, and speed under various operating conditions. In addition to the modelling validation, the transient behavior of the LSPMSM are discussed to describe the possible reasons for its behaviour during transient and steady-state operating conditions. [ABSTRACT FROM AUTHOR]

Modelica is an open-source, object-oriented equation-based modeling language. It is suitable for describing sophisticated dynamic systems (symmetry/asymmetry) as it uses mathematical acausal equations to express physical characteristics. The hydraulic mechanical units (HMU) of gas turbine engine control systems couple the contents of mechanical, hydraulic, symmetry, and other multidisciplinary fields. This paper focuses on the Modelica description method of those HMU models. The content of this work is threefold: firstly, the division form of basic elements in HMU is defined, and the method for describing these element models with Modelica is proposed; secondly, the organization of the element models is defined by using the inheritance characteristics of Modelica, and a lightweight (small code scale) component model is designed; and finally, the causal/acausal connections are designed according to bond graph theory, and the elements and components are integrated into a prototype modeling library. In this paper, the modeling library is verified by comparing simulation results of five typical HMU subsystem models with commercial modeling and simulation software. [ABSTRACT FROM AUTHOR]

Current physical systems are built in more that one coordinate: for example, electrical power systems, aeronautical systems and robotic systems can be modeled in multibond graphs (M B G) . However, in these systems, some elements use only one axis or dimension—for example, actuators and controllers—which can be modeled in bond graphs (B G) . Therefore, in this paper, modeling of systems in multibond graphs and bond graphs ( M B G - B G ) is presented. Likewise, the junction structure of systems represented by ( M B G - B G ) is introduced. From this structure, mathematical modeling in the state space is presented. Likewise, modeling of systems on a platform ( M B G - B G ) can be seen as symmetric to the mathematical model that represents these systems. Finally, a synchronous generator modeled by ( M B G - B G ) as a case study is developed, and simulation results using 20-Sim software are shown. Furthermore, an electrical power system connected to the power supply of a DC motor as another case study is explained. [ABSTRACT FROM AUTHOR]

The bond graph methodology for modelling an integrated energy distillation column is applied in this paper. The distillation column is built by five trays for a binary mixture. However, due to its modular construction in a bond graph, the number of trays can be increased. In order to link the analysis tools of systems modeled in the bond graph to the mathematical model given to a distillation column, a junction structure of the proposed bond graph is presented. Hence, this junction structure is a way to obtain the state space representation of the modeled column in bond graphs. Likewise, it is well known that distillation columns determine a class of nonlinear systems, so throughout this paper, these systems in a bond graph approach can be analyzed. In order to learn the behavior of the distillation column in the physical domain, simulation results using 20-Sim software are shown. In addition, with the simulation of two case studies consisting of two mixtures with different relative volatilities, the versatility of the column model in a bond graph is presented. In both cases, the increase in the feed flow, the mole fraction of the light component in the feed or the distillate reflux that enriches the concentration of light in the column determine an increase in the mole fraction of light in the distillate and in the bottom reflow. Further, the control design for a distillation column in the physical domain can be extended. [ABSTRACT FROM AUTHOR]

As countries attach great importance to the ocean-going navigation capability of ships, the energy consumption of shipborne equipment has attracted much attention. Although energy consumption analysis is a guiding method to improve energy efficiency, it often ignores the dynamic characteristics of the system. However, the traditional dynamic analysis method hardly considers the energy consumption characteristics of the system. In this paper, a new type of electric-driven helicopter traction system is designed based on the ASIST system. Combined with power bond graph theory, a system dynamic modeling method that considers both dynamic and energy consumption characteristics is proposed, and simulation analysis is carried out. The results indicate that the designed traction system in this study displays high responsiveness, robust, steady-state characteristics, and superior energy efficiency. When it engages with helicopter-borne aircraft, it swiftly transitions to a stable state within 0.2 s while preserving an efficient speed tracking effect under substantial load force, and no significant fluctuations are detected in the motor rotation rate or the helicopter movement velocity. Moreover, it presents a high energy utilization rate, achieving an impressive energy utilization rate of 84% per single working cycle. Simultaneously, the proposed modeling methodology is validated as sound and effective, particularly apt for the dynamic and power consumption analysis of marine complex machinery systems, guiding the high-efficiency design of the transmission system. [ABSTRACT FROM AUTHOR]

Many current brain–computer interface (BCI) applications depend on the quick processing of brain signals. Most researchers strive to create new methods for future implementation and enhance existing models to discover an optimal feature set that can operate independently. This study focuses on four key concepts that will be used to complete future works. The first concept is related to potential future communication models, whereas the others aim to enhance previous models or methodologies. The four concepts are as follows. First, we suggest a new communication imagery model as a substitute for a speech imager that relies on a mental task approach. As speech imagery is intricate, one cannot imagine the sounds of every character in every language. Our study proposes a new mental task model for lip-sync imagery that can be employed in all languages. Any character in any language can be used with this mental task model. In this study, we utilized two lip-sync movements to indicate two sounds, characters, or letters. Second, we considered innovative hybrid signals. Choosing an unsuitable frequency range can lead to ineffective feature extractions. Therefore, the selection of an appropriate frequency range is crucial for processing. The ultimate goal of this method is to accurately discover distinct frequencies of brain imagery activities. The restricted frequency range combination presents an initial proposal for generating fragmented, continuous frequencies. The first model assesses two 4 Hz intervals as filter banks. The primary objective is to discover new combinations of signals at 8 Hz by selecting filter banks with a 4 Hz scale from the frequency range of 4 Hz to 40 Hz. This approach facilitates the acquisition of efficient and clearly defined features by reducing similar patterns and enhancing distinctive patterns of brain activity. Third, we introduce a new linear bond graph classifier as a supplement to a linear support vector machine (SVM) when handling noisy data. The performance of the linear support vector machine (SVM) significantly declines under high-noise conditions. To complement the linear support vector machine (SVM) in noisy-data situations, we introduce a new linear bond graph classifier. Fourth, this paper presents a deep-learning model for formula recognition that converts the first-layer data into a formula extraction model. The primary goal is to decrease the noise in the formula coefficients of the subsequent layers. The output of the final layer comprises coefficients chosen by different functions at various levels. The classifier then extracts the root interval for each formula, and a diagnosis is established based on these intervals. The final goal of the last idea is to explain the main brain imagery activity formula using a combination formula for similar and distinctive brain imagery activities. The results of implementing all of the proposed methods are reported. The results range between 55% and 98%. The lowest result is 55% for the deep detection formula, and the highest result is 98% for new combinations of signals. [ABSTRACT FROM AUTHOR]

The main contribution of this article is creating synergy between subjects; this means that students use the same graphical tool in several subjects. So far, the bond graph has not been used in control theory, but it is the "native language" of mechatronics engineers, so we would like to introduce it into the teaching of control theory. The bond graph method is proposed as a novel teaching method to teach mechatronics subjects in the paper. The bond graph is a graphical alternative to ordinary differential equations from a mathematical standpoint. Traditionally, control theory employs ordinary differential equations, as they are familiar to control theorists. However, mathematically, both approaches are equivalent but require a slightly different approach in their application. This article highlights the mathematical similarities between the two approaches while emphasizing the distinctions in graphical representation. Another contribution is that the PID and sliding mode controller are represented using the bond graph method. In the meantime, through the use of practical examples, we effectively illustrate how the same problem can be solved using either approach. In the training materials, the PID controller and an adaptive robust sliding mode controller (ARSMC) with the bond graph are utilized as examples to demonstrate synergy in mechatronics. Finally, we present proof that mechatronic engineers achieve superior outcomes when utilizing the bond graph approach, based on test results from undergraduate students. [ABSTRACT FROM AUTHOR]

In this paper, the bond graph modeling for the control of tracking systems has been applied. The closed loop system is built by the bond graph model of the system to be controlled, an additional bond graph according to the tracking input signal, and feedback gains in the physical domain. Hence, a procedure to obtain the closed loop tracking system is proposed. The proposal of modeling and tracking control systems in this paper determines symmetries in the bond graph approach with respect to the traditional algebraic approach. The great advantage of this graphical approach is that the mathematical determination of the system model is not necessary. Moreover, the coefficients of the characteristic polynomial using unidirectional causal loops of the closed loop system modeled in bond graphs are obtained. A case of study of a DC motor connected to an electrical supply network and a mechanical load is considered. Tracking control for the step, ramp, and acceleration type input signals in a bond graph approach are applied. In order to show the effectiveness of the proposed procedure, the simulation results are shown. [ABSTRACT FROM AUTHOR]

Transmissibility is a mathematical model that relates a subset of a system’s outputs to another subset of outputs of the same system without knowledge of the external excitation or the dynamics of the system. This study investigates fault detection, localization, and mitigation of connected autonomous vehicles (CAV) platoons using transmissibility operators. A CAV platoon is a network of connected autonomous vehicles that communicate together to move in a specific path with the desired velocity. Failure in a physical component of a vehicle, or failure in the form of an internal delay, a cyber-attack, or a communication time-delay affects the safety and security of the CAV platoons. In this paper, we use measurements from sensors available in CAV platoons to identify transmissibility operators, which are used for health monitoring, fault localization, and fault mitigation in the platoon. We first consider the case of vehicle-to-cloud communication (V2C) to monitor the platoon’s health. Then, we assume that the platoon loses communication with the cloud, and we monitor the health of the platoon based on vehicle-to-vehicle (V2V) communication. We apply the proposed technique to a model of the platoon obtained using the bond graph approach, and an experimental setup consisting of three connected autonomous robots. [ABSTRACT FROM AUTHOR]

One of the most fundamental and well-studied problems in Tile Self-Assembly is the Unique Assembly Verification (UAV) problem. This algorithmic problem asks whether a given tile system uniquely assembles a specific assembly. The complexity of this problem in the 2-Handed Assembly Model (2HAM) at a constant temperature is a long-standing open problem since the model was introduced. Previously, only membership in the class coNP was known and that the problem is in P if the temperature is one ( τ = 1 ). The problem is known to be hard for many generalizations of the model, such as allowing one step into the third dimension or allowing the temperature of the system to be a variable, but the most fundamental version has remained open. In this paper, we prove the UAV problem in the 2HAM is hard even with a small constant temperature ( τ = 2 ), and finally answer the complexity of this problem (open since 2013). Further, this result proves that UAV in the staged self-assembly model is coNP-complete with a single bin and stage (open since 2007), and that UAV in the q-tile model is also coNP-complete (open since 2004). We reduce from Monotone Planar 3-SAT with Neighboring Variable Pairs, a special case of 3SAT recently proven to be NP-hard. We accompany this reduction with a positive result showing that UAV is solvable in polynomial time with the promise that the given target assembly will have a tree-shaped bond graph, i.e., contains no cycles. We provide a O (n 5) algorithm for UAV on tree-bonded assemblies when the temperature is fixed to 2, and a O (n 5 log τ) time algorithm when the temperature is part of the input. [ABSTRACT FROM AUTHOR]

In this paper, a new degradation model of the more electrical aircraft (MEA) actuation system is proposed. The bond graph model is used to build the dissimilar redundancy actuation system model, taking into account the degradation behavior (wear, fatigue, aging) of components in the system operation and the fault coupling phenomenon caused by the accumulation of dissipated energy in space and time, and a fault coupling degradation model of the actuation system is established with clear mechanism support. Through the fault mechanism analysis, various fault types are injected into the bond graph model of the actuation system, and the simulation results are compared. The influence of fault propagation on system output is analyzed, the system's reliability is assessed, and the performance evaluation of the actuation system is realized while taking the fault coupling mechanism into account. [ABSTRACT FROM AUTHOR]

Dynamic interaction between train wheel and high-speed slab is an important issue when evaluating the contact force at the wheel–rail interface under the influence of an irregularity either on the train wheel or on the rail. In this paper, an influence of amplitude of irregularity along with the vehicle speed on the dynamics of wheel–rail interaction for high-speed railway tracks is being analyzed. For this purpose, single-wheel high-speed railway (HSR) track interaction models are developed using the bond graph modeling technique. The HSR track model consists of two layers of beam, i.e., rail and concrete slab. Both the rail and slab track is modeled using the Euler–Bernoulli beam theory. The Hertzian contact theory at the wheel–rail interface has been considered for this analysis. The vertical dynamic interaction between a train wheel and a high-speed slab track is compiled in the time domain using a bond graph approach coupled with a technique known as modal superposition. Irregularity present on the wheel is characterized as smooth, moderate, and severe depending upon the variation of irregularity amplitude. An expeditious increase of maximum contact force has been observed between the speed range of 200 and 250 km/h. Beyond the speed of 250 km/h, there is a gradual increment of contact force up to its peak value. When the train speed is beyond 288 km/h, there is a gradual decrease in maximum contact force. This kind of several other useful dynamic responses in terms of wheel acceleration and wheel–rail overlap are also evaluated. [ABSTRACT FROM AUTHOR]

This paper exhibits a study of car passive and active-suspension system to improving drive exhilarate to passengers while also enhancing vehicle stability by decreasing the effect of oscillation on the suspension. Modeling and simulation by using the bond diagram. They much concede a prime arrangement of the machine to the exterior surrounding: street quality, atmospherically circumstances, while guarantying driver as well as passengers, major safeness and more potentially exhilarate. Automotive aid it course manners. The result cleared this action plan at different set during the vehicle mean, but particularly in evolution level. It is also clear the proportion of suspension system's mass to the vehicle's mass. Also graphical representation of suspension system' parameters like vertical passenger displacement, potential energy of mass of suspension system and acceleration. To foretell the comportment of a car, it is necessary to make design, modeling, and simulation. Honda Civic Lx 2019 sedan car has used for modeling, and simulation. [ABSTRACT FROM AUTHOR]

An industrial linear stage is a device that is commonly used in robotics. To be precise, an industrial linear stage is an electro-mechanical system that includes a motor, electronics, flexible coupling, gear, ball screw, and precision linear bearing. A tight fit can provide better precision but also generates a difficult-to-model friction that is highly nonlinear and asymmetrical. Herein, this paper proposes an advanced trajectory controller based on a digital twin framework incorporated with artificial intelligence (AI), which can effectively control a precision linear stage. This framework offers several advantages: detection of abnormalities, estimation of performance, and selective control over any situation. The digital twin is developed via Matlab's Simscape and runs concurrently having a real-time controller. [ABSTRACT FROM AUTHOR]

This paper presents the results of numerical simulations of a nonlinear bistable system for harvesting energy from ambient vibrating mechanical sources. Detailed model tests were carried out on an inertial energy harvesting system consisting of a piezoelectric beam with additional springs attached. The mathematical model was derived using the bond graph approach. Depending on the spring selection, the shape of the bistable potential wells was modified including the removal of wells' degeneration. Consequently, the broken mirror symmetry between the potential wells led to additional solutions with corresponding voltage responses. The probability of occurrence for different high voltage/large orbit solutions with changes in potential symmetry was investigated. In particular, the periodicity of different solutions with respect to the harmonic excitation period were studied and compared in terms of the voltage output. The results showed that a large orbit period-6 subharmonic solution could be stabilized while some higher subharmonic solutions disappeared with the increasing asymmetry of potential wells. Changes in frequency ranges were also observed for chaotic solutions. [ABSTRACT FROM AUTHOR]

In this paper, we propose a domain-independent nonlinear thermoelastic coupling element to enable the realization of a two-way dynamic coupling between the thermal and elastic domains. The implementation of the proposed coupling element in multi-physical systems modeling will provide reversibly conserved power transactions among the existing physical domains (thermal and elastic domains), which is a favorable demand in coupled field dynamic investigations. To guarantee a conserved and continuous power transmission between the thermal and elastic domains, by means of the Bond Graph notation, a reversible multi-dimensional storage element is designed, and the corresponding multi-dimensional constitutive equations are derived that satisfy the Maxwell reciprocity. The power network of each domain of interest is, also, represented in the Bond Graph notation, and the corresponding governing equation of each domain is extracted on the basis of physical system theory. The reversible connectivity of the thermal and elastic domains is then executed via replacing the storage elements of each of the domains with the proposed coupling element. The ensuing model will provide the thermoelastic behavior of the system from the reversible thermal and elastic domains' energetic interactions, which preserves the fundamental physical natures of such phenomena in the model. The generated coupling element will allow the model of each physical domain to remain independent from other existing domains while they are dynamically coupled, which provides a unique benefit for multi-physical phenomena investigations. [ABSTRACT FROM AUTHOR]

Bond graph is a unified graphical approach for describing the dynamics of complex engineering and physical systems and is widely adopted in a variety of domains, such as, electrical, mechanical, medical, thermal and fluid mechanics. Traditionally, these dynamics are analyzed using paper-and-pencil proof methods and computer-based techniques. However, both of these techniques suffer from their inherent limitations, such as human-error proneness, approximations of results and enormous computational requirements. Thus, these techniques cannot be trusted for performing the bond graph based dynamical analysis of systems from the safety-critical domains like robotics and medicine. Formal methods, in particular, higher-order-logic theorem proving, can overcome the shortcomings of these traditional methods and provide an accurate analysis of these systems. It has been widely used for analyzing the dynamics of engineering and physical systems. In this paper, we propose to use higher-order-logic theorem proving for performing the bond graph based analysis of the physical systems. In particular, we provide formalization of bond graph, which mainly includes functions that allow conversion of a bond graph to its corresponding mathematical model (state–space model) and the verification of its various properties, such as, stability. To illustrate the practical effectiveness of our proposed approach, we present the formal stability analysis of a prosthetic mechatronic hand using HOL Light theorem prover. Moreover, to help non-experts in HOL, we encode our formally verified stability theorems in MATLAB to perform the stability analysis of an anthropomorphic prosthetic mechatronic hand. [ABSTRACT FROM AUTHOR]

In this paper, an obstacle avoidance and target tracking method for both indoor and outdoor mobile robots in dynamic environment is presented, and it aims to enhance autonomous navigation capability of such robots. In the proposed method, image processing and machine-learning approaches are considered. Since obstacles have differences in color and texture and in order to identify non-navigable areas, a monocular onboard camera is used to capture the road lanes by dealing with an image processing technique. The position of the robot with respect to road lane center during navigation is calculated on the basis of a proposed fuzzy logic rules set. In order to provide fast and robust computation, the Haar cascade classifier-based machine-learning technique has been exploited to detect the different sizes and shapes of the obstacles faced by the robot during its movement from source to destination. The dynamic model of a four-wheel mobile robot is initially developed using bond graph theory and then, the proposed obstacle-avoidance strategy is applied. The effectiveness and performance of the proposed method are tested under various simulation and experimentation scenarios. The behavior of the mobile robot for detecting and avoiding static obstacle for single and double road lane change environment is analyzed and discussed. [ABSTRACT FROM AUTHOR]

Purpose: Gas turbine blades are subjected to fluctuating gas forces and centrifugal forces, which result into large resonant stresses and further lead to the failure of blades. Nowadays, dry friction damping is frequently applied in gas turbines, especially at hot locations, to reduce resonant stresses. The novelty of the paper lies in simulation of an assembly consists of two gas turbine blades and an under-platform damper through bond graph modelling technique. In this research work, dynamic behaviour of turbine blade and under-platform friction damper are obtained by evaluating their parameters. Method: A lumped parameter model is developed for turbine blades and damper assembly. Further, the values of equivalent damping coefficient (Ceq) for an under-platform friction damper are evaluated through Lazan's law. For simulation, a discrete bond graph model of the turbine blades–damper assembly is created and simulated through Runge–Kutta method. Results and Conclusions: The dynamic parameters viz. displacement, velocity and force on turbine blades, damper's displacement, velocity and frictional force of under-platform damper for all varying values of equivalent damping coefficients (Ceq) are obtained. These evaluated dynamic parameters of turbine blades and under-platform friction damper are further analysed for optimum designing of under platform friction damper to reduce resonant stresses and hence increase the fatigue life of turbine blades. [ABSTRACT FROM AUTHOR]

A fault diagnosis method using bond graphs in an expert system is proposed for a reactor coolant system. Firstly, the time causality graph and the variable relationship graph are derived from the bond graph. Secondly, the fault signature matrix is obtained by combining the change relationship of fault parameters. Finally, the fault signature matrix is used as the rule of the inference engine design in the expert system for fault diagnosis. In this paper, the key equipment of the reactor coolant system is used to verify the fault diagnosis method of the bond graph expert system, and the path reasoning relationship between alarms is obtained, which can accurately obtain the deep knowledge required by the operators. A new idea for fault diagnosis in a nuclear power plant's expert system is provided by this method. [ABSTRACT FROM AUTHOR]

To improve the prediction accuracy of temperature and humidity in typical Chinese solar greenhouses, this paper proposed a new longwave/shortwave radiation modeling method using bond graph. This model takes into account sun position, useful incoming solar radiation model, sky longwave radiation model, inside longwave, and shortwave radiation model. The approach solves the problems caused by underestimating the effects of longwave radiation on night temperature and relative humidity. The study found that after a period of t = 7.5 h, with the increase of sun altitude angle, the internal temperature was significantly affected by the temperature rise of outside environment on sunny day. The sun altitude angle gradually falls over a period of t = 12.5 h (beginning at 12.30 p.m.). The decline in night temperature steadily slowed after a period of t = 20.5 h. On the other hand, the temperature variation has a multi-peak distribution and the warming rate of the CSG slows down on cloudy days. Furthermore, a good agreement between the experimental and simulation data were obtained, with a maximum temperature deviation of 2°C and maximum humidity deviation of 5%. The developed model is a universal and valuable approach that can be used for greenhouse climate simulation. Furthermore, it can be used as a support system during decision-making processes to help manage Chinese solar greenhouses more efficiently, which provides several control perspectives on the low-energy greenhouse in the future. This work has also provided several control perspectives on the low energy greenhouse in the future. [ABSTRACT FROM AUTHOR]

Featured Application: Precise and accurate lower limb rehabilitation in the form of locomotion assistance and gait training through robust control of robotic exoskeletons. Rehabilitation in the form of locomotion assistance and gait training through robotic exoskeletons requires both precision and accuracy to achieve effective results. The essential challenge is to ensure robust tracking of the reference signal, i.e., of the gait or locomotion. This paper presents the design of model-based (MB) and model-free (MF) robust control strategies to achieve desired performance and robustness in terms of transient behavior and steady-state/tracking error, implementable to the locomotion assistance and gait training by exoskeletons. The dynamic responses of the exoskeleton system were investigated with both the control strategies. The study was carried out with a variety of reference signals and performance was evaluated to identify the best suited approach for rehabilitation exoskeletons. In case of the model-based control, a mathematical model of the system was developed using a bond graph modeling technique and a lead compensated H-infinity reference gain controller was designed to ensure robust tracking performance. In the model-free control strategy, however, the system function is approximated using radial basis function neural networks (RBFNNs) and an adaptive proportional-derivative RBFNN controller was designed to achieve the desired results with minimum tracking error. Both strategies make the system robust and stable. However, the MF control strategy is faster for all reference inputs as compared to the MB control strategy i.e., faster to approach the peak value and settle, and rapidly approaches the zero steady-state/tracking error. The rise time in the case of a sinusoidal input for model-free control is 0.4 s faster than the rise time in model-based control. Similarly, the settling time is 3.9 s faster in the case of model-free control, which is a prominent difference and can provide better rehabilitation results. [ABSTRACT FROM AUTHOR]

In this paper, an integrated condition monitoring method combining model-based fault diagnosis and data-driven prognosis is proposed for steer-by-wire (SBW) system. First, the SBW system is modeled by bond graph (BG) technique and a two-degree-of-freedom (2-DOF) state-space model of the vehicle is built. Based on the 2-DOF model, the estimated self-aligning torque is used for the control of feedback motor. The fault detection is carried out by evaluating the analytical redundancy relations derived from the BG model. Since the fault isolation performance is essential to subsequent fault estimation process, a new fault isolation method based on finite state machine is developed to improve the isolation ability by combining the dependent and independent analytical redundancy relations, where the number of potential faults could be decreased. In order to refine the possible fault set to determine the true fault, a cuckoo search (CS)–particle filter is developed for fault estimation. Based on the estimated true fault, prognosis can be implemented which is important to achieve failure prevention and prolong system lifespan. To this end, an optimized extreme learning machine (OELM) is proposed where the input weights and hidden layer biases are optimized by CS. Based on data representing fault values obtained from the fault identification, the OELM model is trained for remaining useful life prediction of failing component. Finally, the proposed methodologies are validated by simulations. [ABSTRACT FROM AUTHOR]

Featured Application: The research results of this paper are mainly applied to the landing assistance of the shipborne helicopter, including the capture and traction of the shipborne helicopter after landing. The shipborne helicopter is an essential maritime combat force of the modern navy. However, as the most advanced shipborne helicopter landing assistance system, the ASIST still suffers from the significant disadvantage of the uncontrollable driving speed of the claw. This paper aims to propose an implementation scheme of the EASIST transmission system by selecting an asynchronous motor as the direct power source to solve the problem. On this basis, the speed controller is built by combining the vector control algorithm with an ANFIS control algorithm. In addition, the capture and traction characteristics of EASIST are analyzed, and the capture track of the claw and the maximum load in the traction process are obtained. Finally, the dynamics model of the transmission system is established by power bond graph theory, and the system simulation test is carried out. Simulation results show that the proposed EASIST reduces the capture time by about 60% and dramatically reduces the capture speed. And when towing the shipborne helicopter, EASIST can keep a good speed-tracking effect under the action of wildly varying load force. The research results of this paper are of great significance to broaden the application scope of ASIST and improve the traction efficiency, which plays a vital role in enhancing the combat effectiveness of shipborne helicopters. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach for remaining useful life prediction that combines a bond graph, the Gaussian Mixture Model and similarity techniques to allow the use of both physical knowledge and the data available. The proposed method is based on the identification of relevant variables that carry information on degradation. To this end, the causal properties of the bond graph (BG) are first used to identify the relevant sensors through the fault observability. Then, a second stage of analysis based on statistical metrics is performed to reduce the number of sensors to only the ones carrying useful information for failure prognosis, thus, optimizing the data to be used in the prognosis phase. To generate data in the different system state, a simulator based on the developed BG is used. A Gaussian Mixture Model is then applied on the generated data for fault diagnosis and clustering. The Remaining Useful Life is estimated using a similarity technique. An application on a mechatronic system is considered for highlighting the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a novel nonlinear bond graph model of the regenerative hydraulic suspension system. The model has been developed in a way that closely follows the physical structure of the underlying system. The proposed regenerative hydraulic suspension bond graph model was simulated for the mathematical approximation of E class road profile according to the ISO 2631–1 standard (10 mm and 3.81 Hz excitation parameters). The obtained simulation results show that the proposed regenerative suspension system can effectively isolate vibrations even on a poor road at a relatively high excitation frequency. The reduction of the vehicle chassis velocity relative to the velocity of the input signal is about 62% (for selected simulation parameters). The proposed regenerative hydraulic system can regenerate a maximum electrical power of 23.9 W and an average electrical power of 19.84 W in an electric generator for a 10 s simulation test. This type of device is more practical to use on lower quality roads for the category of heavy vehicles due to the compromise of vehicle driving comfort and useful power regeneration. [ABSTRACT FROM AUTHOR]

Safety, availability and reliability are the main concern of many industries. Thus, fault detection and isolation of industrial machines, which are in most cases switched systems, is a primary task in many companies. The presented paper proposes a new diagnostic approach for switched systems using two powerful tools: bond graph and observer. A diagnostic layer detects model errors using bond graph, and a smart algorithm identifies and locates faults using observer. Although observers serve as fault detectors, they also have their own errors caused by convergence delay of calculations; even in the case of no sensor defect, the residue does not converge to zero. In this paper, we propose a new method to solve this problem by integrating dynamic thresholds in the detection procedure, which helped to avoid false alarms and ensure a highly reliable diagnosis. [ABSTRACT FROM AUTHOR]

In order to understand and to predict cable effects on structures, three-dimensional numerical models for a stranded cable and a beam–cable system consisting of a cantilever beam and two connected cables are presented. The multibond graph formalism is used to model the coupled cable–beam system, with the cable and beam substructures using 3D rigid lumped segments. The stranded cables are modelled considering the bending stiffness, tension and sag due to self-weight. The generally applicable cable-structure modelling approach in this paper is applied to vibration-based non-destructive evaluation of electrical utility poles, where simulated modal testing of the pole-conductor system is required. Experimental parametrization of a stranded cable is carried out using specially designed apparatus to accurately measure the bending stiffness at different tensions, and to measure the axial stiffness and axial damping. A reduced-scale lab set-up and finite element models are developed for verification of the numerical models. Experimental free and forced vibration testing is performed on individual cantilever beam and stranded cable subsystems, and on the coupled cable–beam system to verify the numerical models in the frequency and time domains. It is concluded that the 3D bond graph models can be used to understand the interaction between cable and structure, allowing prediction of the in-plane and out-of-plane natural frequencies and time response of the connected pole. It is also concluded that by adding the cable to the pole structure, some modes emerge in the eigenvalue solution of the system which may be categorized as cable-dominated modes, pole-dominated or hybrid modes. [ABSTRACT FROM AUTHOR]

Like all physical systems, biological systems are constrained by the laws of physics. However, mathematical models of biochemistry frequently neglect the conservation of energy, leading to unrealistic behaviour. Energy-based models that are consistent with conservation of mass, charge and energy have the potential to aid the understanding of complex interactions between biological components, and are becoming easier to develop with recent advances in experimental measurements and databases. In this paper, we motivate the use of bond graphs (a modelling tool from engineering) for energy-based modelling and introduce, BondGraphTools, a Python library for constructing and analysing bond graph models. We use examples from biochemistry to illustrate how BondGraphTools can be used to automate model construction in systems biology while maintaining consistency with the laws of physics. [ABSTRACT FROM AUTHOR]

The uninterrupted operation of induction motors is crucial for industries, ensuring reliability and continuous functionality. To achieve this, we propose an innovative approach that utilizes an efficiency model-based digital shadow system for in situ failure detection and diagnosis (FDD) in induction motors (IMs). The shadow model accurately estimates IM losses and efficiency across various operational conditions. Our proposed method utilizes efficiency as the primary indicator for fault detection, while losses serve as condition indicators for fault diagnosis based on real-time motor parameters and loss sources. We introduce a bond graph as a fault diagnosis network, linking loss sources, motor parameters, and faults. This interconnected approach is the key aspect of our proposed diagnostic method and aims to be used in fault diagnosis as a general method. A case study of a broken rotor bar is used to validate the proposed method using a dataset of five motors. Among these, one motor operates without failure, while the remaining four exhibit broken rotor faults categorized as 1, 2, 3, and 4. The proposed method achieves 99.99% precision in identifying one to four defective rotor bars in IMs. Comparative analysis demonstrates good performance compared to vibration-based FDD approaches. Moreover, our methodology is computationally efficient and aligned with Industry 4.0 requirements. [ABSTRACT FROM AUTHOR]

In this paper, a new hybrid algorithm, based on multi-objective genetic programming and bond graphs in combination with Monte Carlo simulation, is proposed for Pareto optimal robust design of dynamical systems. For this purpose, first, an embryo model is considered for a dynamical system. Then, genetic programming is used to help this embryo model evolve through generations and achieve an optimum model. It is clear that without considering the uncertain parameters of the designing system, unwanted behaviors could occur. To overcome this, Monte Carlo simulation has been used to minimize the variations of objective functions by generating some samples around the nominal values of the uncertain parameters. In other words, the mean and variance of the objective function are minimized simultaneously through sampling, generated by Monte Carlo simulation, to reach a robust behavior. The proposed algorithm has been employed for robust design of two case studies, namely a closed-loop typewriter drive system and an optimum controller for quarter-car suspension system. A comparison between the results obtained using the proposed algorithm and those obtained through other approaches in the literature shows that more robust behavior in the presence of uncertainties can be observed in the proposed method. [ABSTRACT FROM AUTHOR]

A model based diagnosis for Proton Exchange Membrane (PEM) water electrolyser has been presented in this paper using Linear Fractional Transformation (LFT) bond graph technique. LFT helps in calculating the adaptive thresholds in order to make the diagnosis robust against parameters and measurement uncertainties, hence avoiding false alarms. A modular approach has been followed that allows the model to be adapted to different configurations of PEM electrolyser. The developed diagnosis has been first tested offline by injecting the faults into behavioural model of the PEM electrolyser and then implemented online for a single cell PEM electrolyser. • Software based robust diagnosis has been proposed for PEM electrolyser. • For the first time, diagnosis of cell/stack as well as auxiliaries has been proposed. • The proposed diagnosis is based on Linear Fractional Transformation Bond Graph. • Modular approach makes it adaptable to different configurations of PEM electrolyser. • Tested offline (using behavioural model) and online (on real PEM electrolyser). [ABSTRACT FROM AUTHOR]

The small size of Unmanned Aerial Vehicles (UAVs) incurs many challenges, including concerns of flight stability during turbulence. To address this issue, birds as their natural counterparts have been studied in depth. This paper presents a biologically inspired Gust Mitigation System (GMS) for a flapping wing UAV (FUAV), inspired by the covert feathers of birds. The GMS uses electromechanical (EM) covert feathers that sense the incoming gust and mitigate it through deflection of these feathers. A multibody dynamic model of gust mitigating FUAV is developed by appending models of the subsystems including rigid body, propulsion system, flapping mechanism, and GMS installed to the wings, by using a bond graph modeling approach. The dynamic wing flexibility is modeled with a Euler-Bernoulli beam for realism. The simulation results show that wing flexibility enhances aerodynamic efficiency, and moreover, the performance of the proposed GMS for flexible wings is better than that of rigid wings during gusty airflows. A good agreement between experimental results with these simulations validates the proposed design as well as accuracy of the developed model. [ABSTRACT FROM AUTHOR]

• An electromechanical hydraulic integrated agricultural tractor model by utilizing the bond graph model is developed. • The general power flow model of the electric tractor with mechanical shunt type is also derived. • Using MPGA leads to reduce state of charge (SOC) fluctuations and the remaining SOC is higher, the theoretical hydrogen fuel consumption is decreased. The fuel cell electric tractor has emerged as a new development direction in modern agriculture due to its energy-controllable and emission-reducing advantages. This paper focuses on improving the universality of basic research by studying the fuel cell electric tractor with mechanical shunt type (FCETMST). The bond graph model has the benefits of cross-physical system integration. To fill the gap in general modeling of electric tractors, an electromechanical hydraulic integrated machine model by utilizing the bond graph model, which includes energy system, drive system, lifting system and power take-off (PTO) system, is developed. The general power flow model of the electric tractor with mechanical shunt type is also derived. Lastly, the accuracy of the model is validated by analyzing the tractor's traction characteristics. To further enhance energy efficiency, this paper proposes an energy management strategy (EMS) utilizing a multi-population genetic algorithm (MPGA) and compares it with a power following control strategy (PFCS) for a fuel cell/lithium battery composite energy system. The results base on the co-simulation by using AVL-Cruise and Matlab/Simulink to build a vehicle simulation model and EMS models, respectively, show that under ploughing and transportation conditions, compared with the traditional PFCS, using MPGA leads to reduce state of charge (SOC) fluctuations and the remaining SOC is 11.22 % and 6.1 % higher, respectively. The theoretical hydrogen fuel consumption is decreased by about 26.49 % and 36.21 %, respectively. This study can provide theoretical support for the modeling and energy management optimization of the electric tractor system. [ABSTRACT FROM AUTHOR]

In this paper, a novel Fault Detection and Isolation (FDI) method for Proton Exchange Membrane (PEM) electrolyzers is presented. The challenge of limited availability of labeled fault data is addressed through the utilization of Bond Graphs (BG) and Self-Supervised Learning (SSL). The Linear Fractional Transformation-Bond Graph (LFT-BG) model is employed to generate uncertain residuals and pseudo labels, enabling the training of a deep neural network through self-supervised learning. Additionally, the BG-XAI method is introduced, leveraging eXplainable AI (XAI) and structural equations from Bond Graphs to provide explanations for the decisions made by the deep learning model. The superior performance of the proposed approach, particularly in dealing with limited labeled data, is demonstrated through comparative assessments against various state-of-the-art SSL methods. The demo code of the proposed method is available in this repository: https://github.com/mohan696matlab/SSL_based_Hybrid_FDI. • Uses LFT-bond graph model to generate residuals and pseudo labels for pre-training. • Introduces BG-XAI, a novel explainable AI technique using occlusion. • The proposed hybrid FDI is applied to a PEM electrolyzer stack, showing superior performance. • It deals with limited labeled fault data in renewable energy, offering a reliable solution for diagnosis. [ABSTRACT FROM AUTHOR]

Passive vibration isolation techniques with low-frequency characteristics have been a hot topic in the aerospace field. A hydraulic inertial vibration isolator is a highly effective type of isolator for controlling low-frequency vibrations. It typically consists of a main spring, a minor spring, an inertial mass, and a fluid domain. Due to its multi-domain nature, analyzing the isolation mechanism of this type of isolator is challenging. The bond graph method is employed to establish the dynamic model of the isolator. Subsequently, the state equations of the isolator are derived, and the energy equations of both the mechanical and the fluid parts of the isolator are obtained. Based on this, the energy transfer characteristics between the mechanical and fluid domains inside the isolator under external excitation are discussed. The time-domain response of the forces transmitted to the foundation is analyzed. It is shown that the anti-resonance frequency occurs when the forces transmitted to the foundation generated by the main spring and the fluid pressure are equal to that of the minor spring. To verify the proposed method's correctness, a prototype of the isolator is designed and a carefully designed experiment is conducted. The acceleration transmissibility of the isolator is used to conduct a comparative study. The results show that the theoretical results are in good agreement with the experimental results. To depict the dynamic characteristics of the isolator under large amplitude vibration, the nonlinear dynamic model of the isolator is developed, and the corresponding force transmissibility of the isolator is formulated. The energy flow between the mechanical and the fluid domains under this condition is also analyzed. The results indicate that the energy flow responses exhibit a similar change tendency to the force transmissibility. However, the peak of the energy ratio between the mechanical subsystem and the fluid is the same as the linear condition, suggesting that this value is determined by the amplification ratio of the isolator. This research provides enhanced physical insight to understand the dynamic characteristics of this type of isolator and will help to shorten the design cycle of the isolator. [ABSTRACT FROM AUTHOR]

Computational biology and physiology is an interdisciplinary endeavour, requiring input from biologists, physiologists, mathematicians, chemists, engineers and clinicians. These systems are composed of complex phenomena across disparate temporal and spatial scales, and a holistic understanding of system behaviour typically requires the application of advanced multi-scale models. While many modelling techniques have been used, the bond graph (BG) is the only approach for modelling physical systems, where 'causality' is represented graphically. Additionally, the BG approach with its intrinsic properties allows the modular construction of models and verifying the conservation of mass and energy algorithmically. The BG approach has been widely used in engineering and, more recently, has been increasingly applied to biology and physiological systems. In this review, we briefly introduce the concepts and strengths of BG modelling. Following this, we review the history of BGs in modelling cellular mechanisms, biochemical reactions and musculoskeletal and cardiovascular systems. Then, current developments in BG software are reviewed, and opportunities and perspectives on the future application of BGs are discussed. [ABSTRACT FROM AUTHOR]

Recently, environmental regulations have been strengthened due to climate change. This change comes in a way that limits emissions from ships in the shipbuilding industry. According to these changes, the trend of ship construction is changing installing pollutant emission reduction facilities such as scrubbers or applying alternative fuels such as low sulfur oil and LNG to satisfy rule requirements. However, these changes are focused on large ships. Small ships are limited in size. So, it is hard to install large facilities such as scrubbers and LNG propulsion systems, such as fishing boats that require operating space. In addition, in order to apply the pure electric propulsion method, there is a risk of marine distress during battery discharge. Therefore, the application of the electric–diesel hybrid propulsion method for small ships is being studied as a compromised solution. Since hybrid propulsion uses various energy sources, a method that can estimate effective efficiency is required for efficient operation. Therefore, in this study, a Bond graph is used to model the various energy sources of hybrid propulsion ships in an integrated manner. Furthermore, based on energy system modeling using the Bond graph, the study aims to propose a method for finding the optimal operational scenarios and reduction ratios for the entire voyage, considering the navigation feature of each different maritime region. In particular, the reduction gear is an important component at the junction of the power transmission of the hybrid propulsion ship. It is expected to be useful in the initial design stage as it can change the efficient operation performance with minimum design change. [ABSTRACT FROM AUTHOR]

One of the most important features in the analysis of the singular perturbation methods is the reduction of models. Likewise, the bond graph methodology in dynamic system modeling has been widely used. In this paper, the bond graph modeling of nonlinear systems with singular perturbations is presented. The class of nonlinear systems is the product of state variables on three time scales (fast, medium, and slow). Through this paper, the symmetry of mathematical modeling and graphical modeling can be established. A main characteristic of the bond graph is the application of causality to its elements. When an integral causality is assigned to the storage elements that determine the state variables, the dynamic model is obtained. If the storage elements of the fast dynamics have a derivative causality and the storage elements of the medium and slow dynamics an integral causality is assigned, a reduced model is obtained, which consists of a dynamic model for the medium and slow time scales and a stationary model of the fast time scale. By applying derivative causality to the storage elements of the fast and medium dynamics and an integral causality to the storage elements of the slow dynamics, the quasi-steady-state model for the slow dynamics is obtained and stationary models for the fast and medium dynamics are defined. The exact and reduced models of singularly perturbed systems can be interpreted as another symmetry in the development of this paper. Finally, the proposed methodology was applied to a system with three time scales in a bond graph approach, and simulation results are shown in order to indicate the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

During the metal cutting process, dynamics of a mechanism influence the cutting phenomenon at the contact interface while the contact interaction also has its reciprocal effect on the mechanism. Modeling the dynamics and the contact interaction between the cutting tool and workpiece, causing material removal, is a complex and challenging task. The mechanism of a machine involves a number of interconnected rigid bodies that interact with each other dynamically. Modeling dynamics of such mechanisms is necessary from the point of view of design and analysis. In this paper, the multibond graph approach has been used fxor modeling the dynamics of a power hacksaw machine. The power hacksaw machine is quite commonly used for cutting materials in industries. This graphical approach offers scope for analysis of causality, which is an important aspect of physical systems, and its application, a feature not offered by the energy-based formulations, such as the Euler-Lagrange's method and Hamilton's method. These energy-based formulations, commonly used for modeling dynamics of physical systems, also tend to be too mathematically inclined. MATLAB coding for simulation has been done directly from the multibond graph model without explicitly deriving system equations. The simulation results have been presented, analyzed, and discussed. [ABSTRACT FROM AUTHOR]

The paper presents a detailed numerical and algebraic analysis of potential for improving the step ratio automatic transmission (AT) upshift performance by means of modulating the off-going clutch during the inertia phase. The numerical analysis is based on Pareto optimal frontiers obtained by using the previously developed methods for AT shift control trajectory optimization and piecewise-linear control profile parameter optimization, where the control objectives include minimization of shift time, vehicle root mean square jerk, and dissipated clutch energy. The analysis concerns the following control scenarios related to inertia phase: (1) oncoming clutch control only, (2) combined action of oncoming and off-going clutch, (3) oncoming clutch control extended with engine torque reduction control, and (4) combining all three control actions. The numerical results relate to an advanced 10-speed AT and various single-step and double-step upshifts, with emphasis on 1-3 shift. The numerical analysis results are proven algebraically based on a simplified AT model represented in bond graph form. The presented analysis shows that the off-going clutch can reduce either shift time or root mean square jerk index by introducing power recirculation via the two clutches, which is in turn paid for by certain increase of AT energy loss. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid condition monitoring approach, which integrates bond graph model-based diagnostic technique and data-driven remaining useful life (RUL) prediction, for a nonlinear mechatronic system. In this approach, various degrading faults can be considered and the physical degradation model is not required for RUL prediction. Firstly, an integrated fault signature matrix is proposed by the causal path of bicausal-bond graph model to improve fault isolation performance. After that, a biogeography-based optimization (BBO)-particle filter is developed for fault identification. For prognosis, an optimized extreme learning machine (OELM) is proposed where the hidden layer biases and input weights are optimized by BBO. The fault identification results provide data set to train the OELM for prognosis. Finally, the effectiveness of the approach is verified by simulation and experiment results. • A method combining model-based diagnosis and data-driven prognosis is proposed. • The integrated fault signature matrix is developed for improved fault isolation. • Biogeography-based optimization-particle filter is proposed for fault estimation. • Optimized extreme learning machine is developed to improve prognosis accuracy. [ABSTRACT FROM AUTHOR]

Aiming at the problem of missed diagnosis and misdiagnosis caused by the system uncertainty in the application of analytic redundancy relation based fault diagnosis，this paper introduces the interval analysis into the traditional bond graph linear functional transformation technique（BG-LFT），and proposes an interval redundancy relation based fault diagnosis method. Firstly， the unified modeling for parameter and measurement uncertainty based on BG-LFT are combined with the interval analysis method. Then，the bond graph model is extended to the uncertain bond graph model，and the analytical redundancy relations are transformed into the interval form. Finally，the diagnostic threshold is calculated by the interval mathematical calculation method. The method is applied to the parametric and sensor fault diagnosis of an electro-hydraulic actuator. The results show that compared with single BG-LFT，the proposed method can obtain the diagnosis basis of the electro-hydraulic actuator more effectively，and avoid the interference of system uncertainty to the diagnosis results. [ABSTRACT FROM AUTHOR]

In the context of globalization where new energy vehicles are widely used, this paper proposes a novel mechanical-electro-hydraulic power coupling system for electric vehicles (MEHV). The planetary gear mechanism (PDCM) is integrated with the accumulator, hydraulic pump/motor, battery and motor to realize the mutual conversion of mechanical energy, electric energy and hydraulic energy. Subsequently, a rule-based energy management strategy is established to distribute energy and realize smooth switching in real time. Then, further analysis is carried out on the electro-hydraulic torque distribution. The results illustrate that, the peak torque of the drive motor (DM) can be decreased, and the hydraulic energy can be fully utilized to improve the state of charge (SOC) under appropriate ratio. Simultaneously, to ensure the appropriate electro-hydraulic ratio under complicated conditions, this paper adopts the fuzzy rule-based energy management strategy of multi-parameter input. Ultimately, the actual driving conditions are established using the actual driving data and the strategy. Consequently, the peak torque is significantly lower than pure electric vehicle, the battery energy consumption is reduced by 19.06%. Therefore, the approach proposed in this paper notably improves the running state of the motor, the energy utilization rate, as well as the economy and stability of the vehicle. • A novel mechanical-electro-hydraulic power coupling system is proposed. • A power flow analysis method based on bond graph theory is proposed. • An analysis of electro-hydraulic ratios is presented by a rule-based strategy. • The electro-hydraulic ratio is optimized according to fuzzy control strategy. • Actual results are analyzed by actual data collection and simulation. [ABSTRACT FROM AUTHOR]

This paper aims to improve the design of a seat slider mechanism for an automotive seating system. The seating track mechanism comprises various parts, such as the track bar, upper slider rail, lower slider rail, and locking/unlocking mechanism. The upper rail holds the seat and manikin weight, whereas the lower rail is secured with mounting brackets. A Computer-aided design model of the proposed modified locking/unlocking mechanism of the seating track is created and conducted Finite Element Analysis (FEA). Also, the study includes the motion and dynamic analysis of the seating track mechanism using the bond graph technique by considering the mechanism with an equivalent spring-mass-damper system. The FEA ensured the design strength and its safety regarding failure analysis, whereas the motion analysis confirmed the suitability of the mechanism's kinematics. It is found that the maximum stress is developed at the track bar, i.e., 186.35 MPa, whereas the track displacement reaches its final design position, i.e., 175 mm in 2 s, when the applied force on the track bar is 100 N and on each slider is 20 N. The study ensures an alternative spring-less locking/unlocking mechanism for the seat slider mechanism.

A high-pressure pneumatic pilot-driven on/off valve (HPPV) that quickly switches an air inlet line on and off was designed to meet the requirements of a compressed air ejection device with high pressure, high flow rate, and continuous ejection. An HPPV multi-physics field simulation model was established using AMESim simulation software based on the bond graph modeling approach that considered mechanical, gas flow, pipe heat exchange, and pilot valve operation, and experiments were conducted to check the simulation model accuracy. The effects of real gas thermodynamics, pipeline heat exchange, and pilot valve operation on the simulation model accuracy and those of different initial parameter conditions on the dynamic characteristics of the HPPV were investigated in the validated simulation model. The results indicated that the tolerance between simulation and experiment was less than 7.3%, so the simulation model was realistic and reliable. In addition, among the different influencing factors, the pipeline heat transfer significantly affected the simulation model accuracy, and the tolerance between the simulation results without considering the pipeline heat exchange and the experimental results exceeded 10%. The real gas thermal effect slightly affected the simulation model accuracy, and the tolerance between the simulation results under the action of each gas state equation was less than 3%. The pilot valve operation affected only the opening and closing moments of the HPPV and had no effect on the simulation model accuracy. The dynamic characteristics of the HPPV were stable and reliable under different initial parameter conditions. [Display omitted] • The HPPV were designed and the performances of it was experimented to verify. • The simulation method in this paper can well predict the HPPV behaviors. • The factors affecting the modeling accuracy of HPPV were investigated. • The dynamic characteristics of the HPPV under different conditions are revealed. [ABSTRACT FROM AUTHOR]

An investigation towards diminishing the power fluctuation of an offshore wind turbine using an Accumulator-based Hydro-Mechanical Power Transmission (Ab-HMPT) is reported. The turbine blades and the rotor are assembled with the Ab-HMPT to make a Wind Turbine Power Generation System (WTPGS). The Ab-HMPT comprises a Planetary Gear Train with a single stage (PGTSS) and a Hydraulic Power Transmission (HPT) unit with an accumulator. The PGTSS magnifies the turbine rotor speed, whereas the HPT stabilizes the hydro-motor speed using the accumulator. A dynamical model of the proposed WTPGS is developed and simulated using Bond Graph (BG) technique. Moreover, a suitable On/Off controller is designed to control the charging and discharging operations of the accumulator in the HPT. The simulation response of the hydro-motor speed and the power development from the hydro-motor shaft are almost stable i.e., 16.9 rad/s and 136.7 kW, respectively, whenever the input wind speed is varied from 14 m/s–10.5 m/s. Therefore, uninterrupted power can be supplied to the wind power supply locations without the use of a power grid or an inverter. Additionally, it is found that the hydro-motor speed is five times higher than the Pelton wheel speed obtained from a similar published scheme. Additionally, the influence of various system parameters, such as accumulator initial pressure, pipe flow resistance, pump and motor leakages, etc. are analyzed in order to obtain maximum stable power output from the wind turbines. [ABSTRACT FROM AUTHOR]