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The inaccurate force and position control of tendon sheath system (TSS) due to nonlinear friction during surgery seriously hinders its development in the field of precision surgical robots. To this end, this paper proposes a time-varying bending angle estimation method under the state of sensorless offline identification combined with robot kinematics by analyzing the friction of the TSS and the deformation of the robot during the movement, and establishes a force and position transfer model with time-varying path trajectory (SJM model). The model uses B-spline curve to fit tendon-sheath trajectory. In order to further improve the control accuracy of force and position, a new intelligent feedforward control strategy that integrates the SJM model and a neural network algorithm is proposed. In order to gain an in-depth understanding of the transmission process of force and position and to demonstrate the validity of the SJM model, an experimental platform for the TSS was built. A feedforward control system under the MATLAB environment was built with the aim of verifying the accuracy of the intelligent feedforward control strategy. The system innovatively combines the SJM model with BP and RBF neural networks, respectively. The experimental results showed that the correlation coefficients (R2) of force and position transfer are above 99.10% and 99.48%, respectively. Ultimately, we compared the intelligent feedforward and intelligent control strategy under a single neural network, and observed that the intelligent feedforward control strategy has a better effect.

Lean burning as one of the low-temperature combustion strategies has the potential to reduce pollution emissions and improve fuel efficiency. However, highly diluted mixtures cause internal combust...

Robot-assisted pelvic fracture closed reduction (RPFCR) positively contributes to patient treatment. However, the current path planning suffers from incomplete obstacle avoidance and long paths.A collision detection method is proposed for applications in the pelvic environment to improve the safety of RPFCR surgery. Meanwhile, a defined orientation planning strategy (OPS) and linear sampling search (LSS) are coupled into the A* algorithm to optimise the reduction path. Subsequently, pelvic in vitro experimental platform is built to verify the augmented A*algorithm's feasibility.The augmented A* algorithm planned the shortest path for the same fracture model, and the paths planned by the A* algorithm and experience-based increased by 56.12% and 89.02%, respectively.The augmented A* algorithm effectively improves surgical safety and shortens the path length, which can be adopted as an effective model for developing RPFCR path planning.

Waste-to-energy is considered as an effective way to simultaneously digest the municipal waste and generate useful power. Steam Rankine cycle is conventionally adopted for solid-waste incineration ...

Ti-6Al-4V alloy has low thermal conductivity, poor machinability, and active chemical activity. However, it is easily bonded to tool surface in the cutting process, resulting in drastic tool wear. The friction contact state and friction behavior between the tool and machined surface can be significantly improved when adopting tool with micro texture on the surface. The tools with line texture, regular hexagonal texture, and without texture on the rake face were adopted in this study. The cutting force, tool wear morphology, and friction coefficient of different type of tools are analyzed based on dry cutting test, friction, and wear test of cemented carbide and titanium alloy. The result shows that the cutting force caused by the line-textured tool is the smallest, following by hexagonal-textured tool and no-textured tool. However, large damage would happen at the cutting edge of line-textured tool as the cutting continues, while the damage of hexagonal-textured tool is relatively light. The main cutting force and feed force of the three kinds of tools increase as cutting depth increased, while decrease with the increase of cutting speed. The wear morphology of textured tool is smoother than that of no-textured tool, due to the micro texture can contain debris and reduce friction coefficient. A cutting force equation is established by ridge regression method based on actual cutting data, which provides a new idea for monitoring the tool during cutting process.

In the dry and hard cutting process of hardened steel, the white layer of the machined surface has a great influence on the service performance and life of the part. The cutting force and cutting heat produced in the process are among the important factors affecting the white layer characteristics. In the process of machining, in addition to the cutting parameters, the characteristics of cutting tools can also lead to significant changes in both service performance and part lifetime. Therefore, it is necessary to further study the changes in the cutting force, cutting heat, and white layer characteristics under the influence of the tool characteristics. In this paper, hard cutting tests of hardened steel were carried out by cutting tools (including PCBN tools and ceramic tools) with different thermal conductivities and flank wear under different cutting speeds. The influence of the cutting speed and tool characteristics on the cutting force, flank temperature and white layer characteristics was analyzed, and a prediction model for the white layer thickness was established. It was found that the cutting speed, tool wear degree, and tool thermal conductivity all have a significant influence on the cutting force, cutting temperature, and white layer thickness. Among the results, the thickness of the white layer first increases and then decreases with increasing flank temperature, and the critical temperature at the maximum thickness of the white layer is the actual final temperature of austenite transformation. Changes in the cutting force indirectly affect the temperatures of the austenite and martensite phase transitions, thus affecting the thickness of the white layer. The prediction results show that a fuzzy neural network based on particle swarm optimization can effectively predict the thickness of the white layer.

Pre-ignition is an undesirable ignition event that affects chemical kinetic measurements in chemical reactors. Meanwhile, it appears randomly in engineering systems and is highly relevant to the soft knock or much stronger and detrimental super-knock in modern downsized engines. Currently its origins are still not fully understood. In this study, the role of turbulence in pre-ignition phenomena was experimentally investigated using a novel rapid compression machine. Different turbulent flow fields were achieved through calibrated orifice plates. Stoichiometric isooctane/air mixtures were tested under engine-relevant conditions in a target pressure range of 15–50 bar and a temperature range of 720–860 K. Useful insights into pre-ignition mechanism were obtained by combining instantaneous pressure acquisition with simultaneously recorded high-speed imaging. The experimental results demonstrate that owning to turbulent mixing with colder boundary layers, ignition timing is delayed when compared to ideal homogeneous compression ignition scenarios. However, pre-ignition phenomena can still be observed and become pronounced at lower target pressures with longer ignition delays. Moreover, pre-ignition formation can be characterized by single or multiple spherical flame kernels, distributed discretely inside core mixture or at near-wall regions. Different from the auto-ignition scenarios dominated by the chemical reactivity of test mixture, these pre-ignition flame kernels feature standard deflagration propagation. Finally, a dimensionless scaling analysis shows that pre-ignition formation is closely associated with turbulent length scale and laminar flame thickness.

In proton exchange membrane fuel cells (PEMFC), the design of the cathode flow field is very important, because an excellent flow channel design can not only accelerate the transmission rate of liquid water, but also affect the distribution of electrode reactants and electrode products which influence the electrochemical performance of the fuel cell. This study presents three new channels (models 1,2 and 3), which were created using two unilateral slopes and a bilateral slope structure with tapered tube lengths of 0.4, 1.2 and 0.8 mm, respectively. The dynamic behavior of liquid water under the three design schemes is numerically studied based on the volume of fluid method. And the influence on the performance of fuel cell was analyzed synthetically. The results indicate that the introduction of a tapered and sloping structure can improve the transmission efficiency of the droplets in the flow channel, and the maximum droplet removal time of the new channel can be reduced by 24.4%compare with standard conventional flow channel. The slope structure guides the flow path of water droplet and reduces the occurrence of droplet spatter. Influenced by the slope and tapered structures, the turbulence of airflow near the bottom surface (gas diffusion layer)of the flow channel is enhanced and Oxygen concentration in the cathode is raised, which improves the mass transfer capacity and average current density of reactive surface. In conclusion, the new type of channel with a tapered and sloping structure has a potential to improve the performance of water management in the cathode channel of PEMFC.

In this study, a proton exchange membrane (PEM) fuel cell stack composed of five cells in series is numerically investigated to study the impact of the nonuniform reactant flow rate on the performa...

The high-pressure injection strategy for di-n-butyl ether (DBE)-diesel fuel blends reduces particulate matter emissions. Exhaust gas recirculation (EGR) technology was used to decrease NOx ...

In this paper, a Pareto front (PF)-based sampling algorithm, PF-Voronoi sampling method, is proposed to solve the problem of computationally intensive multi-objectives of medium size. The Voronoi diagram is introduced to classify the region containing PF prediction points into Pareto front cells (PFCs). Valid PFCs are screened according to the maximum crowding criterion (MCC), maximum LOO error criterion (MLEC), and maximum mean MSE criterion (MMMSEC). Sampling points are selected among the valid PFCs based on the Euclidean distance. The PF-Voronoi sampling method is applied to the coupled Kringing and NASG-II models and its validity is verified on the ZDT mathematical cases. The results show that the MCC criterion helps to improve the distribution diversity of PF. The MLEC criterion and the MMMSEC criterion reduce the number of training samples by 38.9% and 21.7%, respectively. The computational cost of the algorithm is reduced by more than 44.2%, compared to EHVIMOPSO and SAO-MOEA algorithms. The algorithm can be applied to multidisciplinary, multi-objective, and computationally intensive complex systems.

This study investigated the effects of cooperative-control of the start of injection (SOI), excess air ratio (λ), internal exhaust gas recirculation (I-EGR), and intake air temperature (IAT) on the combustion and emission characteristics of gasoline compression ignition (GCI) engines, especially regards to the combustion stability and knock characteristics. And optimizing the GCI engine combustion and emissions through the cooperative control of multiple parameters is the innovation of this research. The results showed that advancing the SOI and increasing the I-EGR ratio can significantly expand the low-load limit, but the heating effect of 20% I-EGR only worked when the SOI was earlier. An appropriate increase of λ could increase the maximum brake thermal efficiency (BTE) to 40.06%, but resulted in high-knock probability and high NOx emissions. Rising the IAT was more effective than advancing the SOI in improving combustion fluctuations, but the knock probability and knock intensity were more sensitive to the early SOI. When the SOI varied from 26 °CA BTDC to 30 °CA BTDC, λ was 1–1.5, the I-EGR ratio was 5%–20%, and the IAT was 40–50 °C; the GCI engine can obtain the balance among high thermal efficiency, high combustion stability, low knock probability, and low emissions.

The combination dimethyl carbonate (DMC)/diesel-blended fuels and the exhaust gas recirculation (EGR) can decrease nitrogen oxide (NOX) and soot emissions simultaneously emitted from the compressio...

Pine oil is mainly produced from the pine tree, which has some prominent fuel-related properties, such as lower boiling point and viscosity than those of the pure diesel. Particularly, its low heating value is similar to that of diesel. In addition, pine oil and diesel can be mixed in any ratio, and the engine can directly burn the pine oil/diesel mixtures without any further modification. Therefore, pine oil is considered to be a promising additive to diesel fuel. However, when pine oil is fueled in a diesel engine via single injection the engine NOX emissions deteriorate. In this present study, the effects of pilot injection (PI) strategies, including pilot injection rate (PIR) and pilot-main interval (PMI) on energy distribution, emissions and combustion were explored in a diesel engine fueling with diesel/pine oil mixtures at low-load condition. Three test fuels were pure diesel (denoted as P0), a mixture of 80% diesel and 20% pine oil (denoted as P20), and 60% diesel and 40% pine oil (denoted as P40), respectively. The results showed that, after utilizing the PI strategies, the peaks of in-cylinder pressure of the three fuels increased compared to single injection, while the maximum pressure rise rates decreased along with an increase in the break thermal efficiency (BTE). After blending pine oil in pure diesel, both the soot and CO emissions were reduced, although the NOX and THC emissions slightly increased. The small PMI strategies could reduce the energy loss of THC, CO emissions and friction, and improve BTE. However, the soot emission increased. At low-load condition, when fueling with P20 blended fuel and using small PMI strategies, the system could achieve higher thermal efficiency and lower soot-NOX emissions than the strategy employing pure diesel.

n-Pentanol exhibits some advantageous fuel properties, such as a higher energy density, lubricity, viscosity, and low hygroscopicity, when compared to short-chain alcohols. It is miscible with pure diesel in large proportions and burns directly on diesel engines. Therefore, n-pentanol is considered to be a promising diesel fuel additive. However, the differences between the chemical and physical properties of n-pentanol and commercial diesel affect the spray, combustion, and emissions performance of commercial diesel engines. In this study, visualization and engine experimental test methods were used to study the spray, combustion, and emissions performance of diesel/n-pentanol mixtures. The results showed that the atomization characteristics of diesel/n-pentanol mixtures were better than those of diesel. As the engine load increased, the maximum in-cylinder pressure and heat release rate increased. The brake specific fuel consumption (BSFC), nitrogen oxide (NOX), hydrocarbons (HC), and carbon monoxide (CO) emissions decreased, but soot emissions increased. Compared to diesel fuel, adding n-pentanol to pure diesel resulted in a decrease in soot emissions, while the BSFC, HC, and NOX emissions increased. Upon adding 50% n-pentanol to pure diesel (P50), the soot emissions decreased by up to 77.15% and the brake thermal efficiency (BTE) decreased by 1.86%. In summary, P50 could be burned directly on the diesel engine without any modifications, which can significantly reduce soot emissions; in this case, the BTE experienced only a slight decrease.

Strong knocking combustion has become the greatest challenge for advanced internal combustion engines to pursue thermal efficiency limits at high power density conditions. Arising from enclosed space and extreme combustion situations, the fundamental mechanism for strong knocking combustion has still not been fully understood. In this study, synchronization measurement was performed through simultaneous pressure acquisition and high-speed direct photography, and knocking experiments were comparatively conducted under spark-ignition (SI) and compression-ignition (CI) conditions in a high-strength optical rapid compression machine (RCM) with flat piston design. Strong knocking phenomena were reproduced through varying initial thermodynamic conditions, and localized autoignition (AI) initiation and reaction wave evolutions were visualized, companied by synchronous pressure and temperature trajectories. The results show that compared with initial temperature, initial pressure and equivalence ratio exhibit greater influence on the variations of knocking severity. The weighting of different contributors can be further quantified by an effective energy density that shows positive but nonlinear correlations with knocking severity. However, the distinctions between CI and SI knocking characteristics at identical effective energy density also reflect the essential role of the interplay between primary flame propagation and end-gas AI progress. Visualized combustion images show that through improving end-gas thermodynamic state and reactivity sensitivity, the primary flame propagation can enhance localized AI initiation and secondary intensive AI evolutions, facilitating combustion mode transitions into developing detonation. The significant influence of primary flame propagation is diminished until ignition delay time becomes sufficiently short. Finally, with estimated thermal heterogeneities in flat-piston RCM configurations, the ignition modes of strong knocking cycles are quantified by a non-dimensional ignition regime diagram, and favorable scaling agreements with strong and mixed ignition regimes are observed.

Particulate matter (PM) emitted from conventional diesel engines has significant deteriorating effects on natural environment and human health. Among alternative oxygenated fuels, polyoxymethylene dimethyl ether (PODE) is a novel renewable fuel with high cetane number, oxygen content and volatility, and has prominent potential for reducing the PM emissions. In this study, the influences of fuel injection parameters, including injection pressure and injection timing on the reduction of PM emissions were explored for a four-cylinder diesel engine fueled with PODE/diesel blends at various engine loads. The three blends were the pure diesel (denoted as P0), a mixture of 80% diesel and 20% PODE (denoted as PD20), and the mixture of 70% diesel and 30% PODE (denoted as PD30). The results showed that adding PODE to diesel resulted in a reduction in both the total particle number concentration (PNC) and the particle mass concentration (PMC) at all loads. For the PODE/diesel blends, at low load and higher injection pressures, the PMC further decreased, although the value of PNC drastically increased. For the PODE/diesel blends, at medium load and higher injection pressures, both the PNC and PMC values decreased. When the injection pressure was higher than 120 MPa, it could not continuously reduce PNC. Furthermore, for the PODE/diesel blends, at high load and high injection pressures, both the PNC and PMC values greatly decreased. The PODE/diesel blends coupled with the retarded injection timing could reduce the PNC and PMC values, but when the injection timing occurred too close to the top dead center (TDC), the PNC value increased. In addition, as the injection timing was closer to TDC, the effect of the addition of PODE in diesel fuel on reducing PNC and PMC became more significant.

A diesel/natural gas (NG) dual-fuel engine is regarded as an appealing option to reduce emissions while maintaining high thermal efficiency. In this study, a reduced n-heptane–n-butylbenzene–NG–polycyclic aromatic hydrocarbon (PAH) mechanism with 746 reactions and 143 species was developed for predicting the combustion characteristics and emission in dual-fuel engines. A mixture of methane, ethane, and propane was used to model the NG, and a mixture of n-heptane and n-butylbenzene was used to model the diesel. This mechanism was based on a reduced n-heptane–PAH mechanism, and the detailed mechanisms of n-butylbenzene and NG were reduced using the methods of directed relation graph with error propagation (DRGEP), rate of production (ROP), and sensitivity analysis. The key kinetic parameters of the model were optimized and adjusted according to the results of sensitivity analysis. The final optimized dual-fuel mechanism was verified against ignition delay, laminar flame speed, and homogenous charge compression ignition (HCCI) engine combustion, and a good prediction was obtained. Finally, the present mechanism was coupled into the CFD software to simulate the combustion characteristics and emission of a dual-fuel engine under four different NG substitution rates. The simulation results are consistent with the experimental data of emissions and combustion characteristics, indicating that the current mechanism can be applied to simulate practical diesel/NG dual-fuel engines.