Increase In Speed Research Articles

Study of Temperature Drop Region in Transitional Region in Fluid-film Thrust Bearings

Abstract A thrust bearing is a type of rotary bearing that permits rotation between parts and is designed to support a load parallel to the axis of rotation. There is a temperature drop region with the increase in speed. However, previous researchers mainly showed such temperature drop experimentally, and the physics causing such temperature drop is not understood. A full fluid-solid CFX model was developed for a center pivot, tilting pad, and fluid-film thrust-bearing experimental model to study the physics of temperature drop in the transitional region. A novel physics of causing temperature drop in the transitional region was proposed, analyzed, and verified.

Six types of spin solitons in three-component Bose–Einstein condensates

Exact analytical solutions are good candidates for studying and explaining the dynamics of solitons in nonlinear systems. We further extend the region of existence of spin solitons in the nonlinearity coefficient space for the spin-1 Bose–Einstein condensate. Six types of spin soliton solutions can be obtained, and they exist in different regions. Stability analysis and numerical simulation results indicate that three types of spin solitons are stable against weak noise. The non-integrable properties of the model can induce shape oscillation and increase in speed after the collision between two spin solitons. These results further enrich the soliton family for non-integrable models and can provide theoretical references for experimental studies.

Study on the impact of ultrasonic vibration-assisted grinding of glass-ceramics on surface/subsurface damage mechanism

PurposeAn investigation was conducted into the impact of various process parameters on the surface and subsurface quality of glass-ceramic materials, as well as the mechanism of material removal and crack formation, through the use of ultrasonic-assisted grinding.Design/methodology/approachA mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. A series of simulations and experiments were conducted to investigate the impact of process parameters on crack depth, surface roughness, and surface topography during ultrasonic-assisted surface and axial grinding. Additionally, the mechanism of crack formation was explored.FindingsDuring ultrasonic-assisted grinding, the average grinding forces are between 0.4–1.0 N, which is much smaller than that of ordinary grinding (1.0–3.5 N). In surface grinding, the maximum surface stresses between the workpiece and the tool gradually decrease with the tool speed. The surface stresses of the workpiece increase with the grinding depth, and the depth of subsurface cracks increases with the grinding depth. With the increase of the axial grinding speed, the subsurface damage depth increases. The roughness increases from 0.780um/1.433um.Originality/valueA mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. The deformation involved in the grinding process is large, and the FEM-SPH modeling method is used to solve the problem that the results of the traditional finite element method are not convergent and the calculation efficiency is low.

Comparison of numerical calculations and ALOHA modeling in consequence assessment of chlorine gas emissions from ethylene dichloride reactors.

Incidents involving chemical storage tanks in the petrochemical industry are significant events with severe consequences. Within the petrochemical industry, EDC is a sector that produces ethylene dichloride through the reaction of chlorine and ethylene. The present research was conducted to evaluate the consequences of chlorine gas released from the EDC reactor in a petrochemical industry in southern Iran. Data regarding reactor specifications were obtained from the factory's technical office, while climatic data was acquired from the Meteorological Organization. The consequences of chlorine gas release from the reactor were assessed in four predefined scenarios using numerical calculation methods and modeling with the ALOHA software. The numerical calculation method involved thermodynamic fluid path analysis, discharge coefficient calculations, and wind speed impact analysis. The hazard radius was determined based on the ERPG1-2-3 index. Results showed that in the scenario of chlorine gas release from EDC reactors, according to the ALOHA model, an increase in wind speed from 3 to 7m/h led to an expanded dispersion radius. At a radius of 700m from the reactor, the maximum outdoor concentration reached 3.12ppm, decreasing to 2.27ppm at 800m and further to 1.53ppm at 1000m. The comparison of numerical calculations and modeling using the ALOHA software indicates the desirable conformity of the results with each other. The R2 coefficient for evaluating the conformity of the results was 0.9964, indicating the desired efficiency of the model in evaluating the consequences of the release of toxic gasses from the EDC tank. The results of this research can be useful in designing the site and emergency response plan.

When can we Kick (Some) Humans “Out of the Loop”? An Examination of the use of AI in Medical Imaging for Lumbar Spinal Stenosis

AbstractArtificial intelligence (AI) has attracted an increasing amount of attention, both positive and negative. Its potential applications in healthcare are indeed manifold and revolutionary, and within the realm of medical imaging and radiology (which will be the focus of this paper), significant increases in accuracy and speed, as well as significant savings in cost, stand to be gained through the adoption of this technology. Because of its novelty, a norm of keeping humans “in the loop” wherever AI mechanisms are deployed has become synonymous with good ethical practice in some circles. It has been argued that keeping humans “in the loop” is important for reasons of safety, accountability, and the maintenance of institutional trust. However, as the application of machine learning for the detection of lumbar spinal stenosis (LSS) in this paper’s case study reveals, there are some scenarios where an insistence on keeping humans in the loop (or in other words, the resistance to automation) seems unwarranted and could possibly lead us to miss out on very real and important opportunities in healthcare—particularly in low-resource settings. It is important to acknowledge these opportunity costs of resisting automation in such contexts, where better options may be unavailable. Using an AI model based on convolutional neural networks developed by a team of researchers at NUH/NUS medical school in Singapore for automated detection and classification of the lumbar spinal canal, lateral recess, and neural foraminal narrowing in an MRI scan of the spine to diagnose LSS, we will aim to demonstrate that where certain criteria hold (e.g., the AI is as accurate or better than human experts, risks are low in the event of an error, the gain in wellbeing is significant, and the task being automated is not essentially or importantly human), it is both morally permissible and even desirable to kick the humans out of the loop.

Shaking Tables Test on Seismic Responses of a Long-Span Rigid-Framed Bridge Considering Traveling Wave Effect and Soil–Structure Interaction

The traveling wave effect and soil–structure interaction have significant influence on the seismic response of large-span bridges with complex site conditions. In this paper, a 1/10 scaled-down large-span rigid-framed bridge model was designed and fabricated, and a shaking tables test considering the traveling wave effect and soil–structure interaction was carried out on a large-scale continuous rigid bridge model by a real-time substructure hybrid test technique. Influences of the traveling wave effect and soil–structure interaction on the seismic responses of the rigid-framed bridge specimen were systematically analyzed with experimental data. The test results showed that when the apparent wave speed was small, the traveling wave effect increased the seismic responses of the rigid-framed bridge. With the increase in apparent wave speed, the structural response under traveling wave excitation and uniform excitation was basically the same. The SSI effect lead to a great change in the seismic input peaks and spectral characters at the bottom of the pier, and increased the seismic responses of the rigid-framed bridge. When both traveling wave and the SSI effect were considered, there was a phase difference in the seismic excitation. The dynamic responses of a continuous rigid-framed bridge could not be simply obtained by superposition of the separate traveling wave effect or SSI effect. Meanwhile, the real-time substructure test method in this paper solved the problems that the traditional soil box experiment cannot be applied to the test of a large-scale model, the soil and bridge structure find it difficult to meet the unified similarity ratio, and the boundary conditions are difficult to simulate accurately.

A Recognition and Classification Method for Underground Acoustic Emission Signals Based on Improved CELMD and Swin Transformer Neural Networks

To address the challenges in processing and identifying mine acoustic emission signals, as well as the inefficiency and inaccuracy issues prevalent in existing methods, an enhanced CELMD approach is adopted for preprocessing the acoustic emission signals. This method leverages correlation coefficient filtering to extract the primary components, followed by classification and recognition using the Swin Transformer neural network. The results demonstrate that the improved CELMD method effectively extracts the main features of the acoustic emission signals with higher decomposition accuracy and reduced occurrences of mode mixing and end effects. Furthermore, the Swin Transformer neural network exhibits outstanding performance in classifying acoustic emission signals, surpassing both convolutional neural networks and ViT neural networks in terms of accuracy and convergence speed. Moreover, utilizing preprocessed data from the improved CELMD enhances the performance of the Swin Transformer neural network. With an increase in data volume, the accuracy, stability, and convergence speed of the Swin Transformer neural network continuously improve, and using preprocessed data from the enhanced CELMD yields superior training results compared to those obtained without preprocessing.

Crystallographic Texture Evolution in 3D Printed Polyethylene Reactor Blends.

In this work, crystallographic texture evolution in 3D printed trimodal polyethylene (PE) blends and high-density PE (HDPE) benchmark material were investigated to quantify the resulting material anisotropy, and the results were compared to materials made from conventional injection molded (IM) samples. Trimodal PE reactor blends consisting of HDPE, ultrahigh molecular weight PE (UHMWPE), and HDPE_wax have been used for 3D printing and injection molding. Changes in the preferred orientation and distribution of crystallites, i.e., texture evolution, were quantified utilizing the wide angle X-ray diffraction through pole figures and orientation distribution functions (ODFs) for 3D printed and IM samples. Since the change in weight-average molecular weight (Mw) of the blend was expected to significantly affect the resulting crystallinity and orientation, the overall Mw of the trimodal PE blend was varied while keeping the UHMWPE component weight fraction to 10% in the blend. The resulting texture was analyzed by varying the overall Mw of the trimodal blend and the process parameters in 3D printing and compared to the texture of conventional IM samples. The printing speed and orientation (defined with respect to the axis along the length of the samples) were used as the variable process parameters for 3D printing. The degree of anisotropy increases with an increase in the nonuniform distribution of intensities in pole figures and ODFs. All the highest intensity major texture components in IM and 3D printed samples (0° printing orientation) of reactor blends are observed to have crystals oriented in [001] or [001̅]. Overall, for the same throughput, 3D printed samples in the 0° orientation showed greater texture evolution and higher anisotropy compared to IM samples. Most notably, an increase in 3D printing speed increased the crystalline distribution closer to the 0° direction, increasing the anisotropy, while deviation from this printing orientation reduced crystalline distribution closer to the 0° direction, thus increasing isotropy. This demonstrates that tailoring material properties in specific directions can be achieved more effectively with 3D printing than with the injection molding process. Change in the overall Mw of the trimodal PE blend changed the preferential orientation distribution of the crystal planes to some degree. However, the degree of anisotropy remained the same in almost all cases, indicating that the effect of molecular weight distribution is not as significant as the printing speed and printing orientation in tailoring the resulting properties. The 3D printing process parameters (speed and orientation) were shown to have more influence on the texture than the material parameters associated with the blend.

High–speed train crash safety assessment for Train–moose collisions

High–speed train crash safety assessment for Train–moose collisions

Study on ice resistance of Antarctic krill ship with trawl under floating ice sea conditions

IntroductionThis study focused on a Chinese Antarctic krill vessel utilising continuous pumping fishing technology. The resistance characteristics of Antarctic krill ships trawling in floating ice areas is of great significance for the navigation and fishing of krill ships in ice areas.MethodsFirstly, MATLAB programming using discrete elements combined with genetic algorithms was used to construct a normal distribution ice flow model. Secondly, a fluid-structure coupling interface is created through the contact between the fluid and the trawl grid, and the displacement and resistance of the trawl grid are evaluated on the shared interface. Finally, the effects of ice density and ship sailing speed on ice resistance were studied.Results and discussionThe results of the calculations results show that ice resistance is positively related to the concentration and speed of floating ice, moreover, there is a special speed point where ice resistance increases rapidly. As the speed increases, the proportion of trawl resistance to the total resistance continues to increase, while the proportion of ice resistance continues to decrease. This paper provides a reference for the navigation and fishing resistance assessment of Antarctic krill ships in floating ice areas.

Kinematics-Based Design Method and Experimental Validation of Internal Meshing Screw for High-Viscosity Fluid Mixing

The challenge of mixing high-viscosity materials is a common issue encountered in the manufacturing process of food materials. The advantages of the internal meshing screw mixer have led to its adoption in various manufacturing processes, but it has yet to be implemented in the food industry. The paper presents a design method for an internal meshing screw mixer based on kinematic principles. The mixer features a helical chamber created by alternating volumes formed by the stator and rotor, establishing an extension-dominated environment for mixing high-viscosity fluids. A kinematic model based on the internal cycloid principle was established, providing trajectories and equations for key points on the rotor, simulating both its rotation and revolution processes, and revealing the velocity variations at different points on the rotor. Based on the kinematic analysis results, a stator and rotor design method was developed according to relevant functional divisions. To achieve the desired motion effects, transmission and support devices were designed, and the relationship between the transmission device and the internal cycloid surface of the fixed rotor was established. The mixer’s application and mixing effectiveness in the food industry were validated using corn syrup and flour. Experimental results showed that the extensional mixer described in the paper effectively mixed high-viscosity fluids while also efficiently blending fine powders. Slurry viscosity was tested with a rheometer at different speeds with an eccentric rotor mixer. Results showed that viscosity decreased with increasing shear rate, with a more pronounced decrease at higher shear rates. The apparent viscosity trend remained consistent at different speeds, although variations were observed at lower shear rates, especially concerning speed. The non-Newtonian fluid index exhibited minimal variations at different speeds, while the consistency coefficient showed significant fluctuations. The mixing uniformity index of the slurry was used to evaluate the mixing uniformity and dispersion uniformity of this extensional mixer. At different rotational speeds, the density of the slurry changes little. The uniformity index of mixing decreases gradually with the increase of rotational speed, reaching its maximum at 15 r/min. The overall trend of the uniformity index decreases with increasing rotational speed, indicating a decrease in density uniformity. A peak appears at 45 r/min, possibly due to the maximum values of elongation rate and shear rate at this speed. As the rotational speed increases, the residence time of the material in the mixer decreases, which may be the main reason for the decrease in mixing uniformity. These findings provide valuable insights into the design and utilization of extension-dominated screw mixers within the food industry, laying a solid foundation for future research and practical applications in this field.

Исследование воздействия критических температур внешней среды на сгущенное молоко с сахаром

The purpose of research is to study the impact of critical high-positive and low-negative environmental temperatures on the thermodynamic parameters of sweetened condensed milk (SCM), packaged in cans placed in transport containers. Objectives: determination of the values of average volumetric temperatures of SCM depending on the type of thermal effect; establishing the influence of the location of the product in the transport package on the average heating/cooling rate of the food system; identification of moisture crystallization criteria values. The object of the study is SCM, packed in tin cans, which were placed in transport packaging. The average volume temperature was measured thermographically using a logger. 4 cycles of thermal exposure were used, °C: [+5↑+50↓+5], [+5↑+50↓–50↑+5], [+5↓–50↑+5], [+5↓– 50↑+50↓+5]. For the range of 100 °C, an almost 2-fold increase in the average speed (1.6–2.6 °C/h) was established when heating [–50↑+50] relative to the average speed (0.8–1.3 °C/h) during cooling [+50↓–50], which is determined by the state of each component of the condensed milk-sugar system at a specific temperature point. At [+5↑+50↓+5] or [+5↓–50↑+5] for the central cans of the middle row, the duration of exposure was shorter (58 h 28 min 48 s and 115 h 19 min 12 s) than for the cans from the top row (78 hours 25 minutes 00 seconds and 124 hours 06 minutes 24 seconds). At [+5↑+50↓–50↑+5], the longest process duration was observed in the middle row consumer packaging. For the same tin, the shortest duration was revealed when exposed to temperatures in the opposite order. In the heating-freezing cycle, a decrease in the temperature of nucleation and phase transition was noted for the central and peripheral positions in consumer packaging and a decrease in the indicated thermodynamic characteristics in consumer packaging within the group for the top row, but an increase – for the middle. In the freeze-heat cycle in consumer packaging within a group package, a classical model of freezing was observed with a decrease in the temperature of nucleation and phase transition.

Simulation Study on Combustion Performance of Ammonia-Hydrogen Fuel Engines

Ammonia is a very promising alternative fuel for internal combustion engines, but there are some disadvantages, such as difficulty in ignition and slow combustion rate when ammonia is used alone. Aiming to address the problem of ammonia combustion difficulty, measures are proposed to improve ammonia combustion by blending hydrogen. A one-dimensional turbocharged ammonia-hydrogen engine simulation model was established, and the combustion model was corrected and verified. Using the verified one-dimensional model, the effects of different ratios of hydrogen to ammonia, different rotational speeds and loads on the combustion performance are investigated. The results show that the ignition delay and combustion duration is shortened with the increase of the hydrogen blending ratio. The appropriate amount of hydrogen blending can improve the brake’s thermal efficiency. With the increase in engine speed, increasing the proportion of hydrogen blending is necessary to ensure reliable ignition. In conclusion, the ammonia-hydrogen fuel engine has good combustion performance, but it is necessary to choose the appropriate hydrogen blending ratio according to the engine’s operating conditions and requirements.

Beamforming for Sensing: Hybrid Beamforming based on Transmitter-Receiver Collaboration for Millimeter-Wave Sensing

Previous mmWave sensing solutions assumed good signal quality. Ensuring an unblocked or strengthened LoS path is challenging. Therefore, finding an NLoS path is crucial to enhancing perceived signal quality. This paper proposes Trebsen, a Transmitter-REceiver collaboration-based Beamforming scheme SENsing using commercial mmWave radars. Specifically, we define the hybrid beamforming problem as an optimization challenge involving beamforming angle search based on transmitter-receiver collaboration. We derive a comprehensive expression for parameter optimization by modeling the signal attenuation variations resulting from the propagation path. To comprehensively assess the perception signal quality, we design a novel metric perceived signal-to-interference-plus-noise ratio (PSINR), combining the carrier signal and baseband signal to quantify the fine-grained sensing motion signal quality. Considering the high time cost of traversing or randomly searching methods, we employ a search method based on deep reinforcement learning to quickly explore optimal beamforming angles at both transmitter and receiver. We implement Trebsen and evaluate its performance in a fine-grained sensing application (i.e., heartbeat). Experimental results show that Trebsen significantly enhances heartbeat sensing performance in blocked or misaligned LoS scenes. Comparing non-beamforming, Trebsen demonstrates a reduction of 23.6% in HR error and 27.47% in IBI error. Moreover, comparing random search, Trebsen exhibits a 90% increase in search speed.

Tibial strains are sensitive to speed, but not grade, perturbations during running.

A fatigue-failure process is hypothesized to govern the development of tibial stress fractures, where bone damage is highly dependent on the peak strain magnitude. To date, much of the work examining tibial strains during running has ignored uphill and downhill running despite the prevalence of this terrain. This study examined the sensitivity of tibial strains to changes in running grade and speed using a combined musculoskeletal-finite element modeling routine. Seventeen participants ran on a treadmill at ±10°, ±5°, and 0°; at each grade, participants ran at 3.33 ms-1 and at a grade-adjusted speed -2.50 and 4.17 ms-1 for uphill and downhill grades, respectively. Force and motion data were recorded in each grade and speed combination. Muscle and joint contact forces were estimated using inverse-dynamics-based static optimization. These forces were applied to a participant-adjusted finite element model of the tibia. None of the strain variables (50th and 95th percentile strain and strained volume ≥4000 μɛ) differed as a function of running grade; however, all strain variables were sensitive to running speed (F ≥ 9.59, p ≤ 0.03). In particular, a 1 ms-1 increase in speed resulted in a 9% (≈260 μɛ) and 155% (≈ 600 mm3) increase in peak strain and strained volume, respectively. Overall, these findings suggest that faster running speeds, but not changes in running grade, may be more deleterious to the tibia. • High-magnitude tibial strains that are implicated in stress-fracture development were sensitive to changes in running speed but not grade. • The majority of the variance in measures of tibial strain was accounted for by individual subject variation, reinforcing the importance of inherent musculoskeletal properties in determining the bone strain environment.

Deep learning-based inverse design of multi-functional metasurface absorbers.

A novel approach-integrating a simulated annealing (SA) algorithm with deep learning (DL) acceleration-is presented for the rapid and accurate development of terahertz perfect absorbers through forward prediction and backward design. The forward neural network (FNN) effectively deduces the absorption spectrum based on metasurface geometry, resulting in an 80,000-fold increase in computational speed compared to a full-wave solver. Furthermore, the absorber's structure can be precisely and promptly derived from the desired response. The incorporation of the SA algorithm significantly enhances design efficiency. We successfully designed low-frequency, high-frequency, and broadband absorbers spanning the 4 to 16 THz range with an error margin below 0.02 and a remarkably short design time of only 10 min. Additionally, the proposed model in this Letter introduces a novel, to our knowledge, method for metasurface design at terahertz frequencies such as the design of metamaterials across optical, thermal, and mechanical domains.

Phase Formation and Magnetic Properties of (Y1−xSmx)Co5 Melt-Spun Ribbons

Using X-ray diffraction (XRD) and a vibrating sample magnetometer (VSM), the effects of Sm substitution, wheel speed, and annealing temperature on the phase formation and magnetic properties of (Y1−xSmx)Co5 (x = 0.2, 0.3, 0.4, 0.5) melt-spun ribbons were investigated. The results indicate the following: (1) With the increase in Sm substitution, it was found that (Y1−xSmx)Co5 ribbons are entirely composed of the (Y-Sm)Co5 phase with a CaCu5-type structure. Additionally, the coercivity gradually increases, while the remanence and saturation magnetization gradually decrease. (2) As the wheel speed increases, the (Y1−xSmx)Co5 ribbons exhibit an increasing proportion of (Y-Sm)Co5 phase until reaching a speed of 40 m/s, where they are entirely composed of the (Y-Sm)Co5 phase. Magnetic measurements show that the coercivity (Hcj) and remanence (Br) of (Y0.5Sm0.5)Co5 ribbons increase gradually with increasing wheel speed, while saturation magnetization decreases. The variation in magnetic properties is mainly attributed to the formation of nucleation centers for reversed magnetic domain (2:7 and 2:17 phases); (3) (Y0.5Sm0.5)Co5 ribbons are composed of the (Y-Sm)Co5 phase and a small amount of the Sm2Co7 phase after annealing at 550 °C, 600 °C, and 650 °C. Temperature elevation promotes crystallization of the amorphous phase, resulting in a gradual decrease in coercivity, while the remanence and saturation magnetization exhibit an overall increasing trend. Through continuous optimization of the process, favorable magnetic properties were achieved under the conditions of a 0.5 Sm substitution level, a wheel speed of 40 m/s, and an annealing temperature of 550 °C, with a coercivity of 7.98 kOe, remanence of 444 kA/m, and saturation magnetization of 508 kA/m.

Experimental study of hydraulic lifting platform based on multi-ring disc magnetorheological valve

To enhance the operational capabilities of a hydraulic lifting apparatus, a hydraulic lifting platform was engineered based on a multi-ring disc magnetorheological valve. The pressure drop characteristics of the multi-ring disc magnetorheological valve were determined through theoretical analysis, supplemented by magnetic field simulations to assess its performance. The effects of different currents on the stability and response time of the hydraulic lifting platform are studied, and the control accuracy of the hydraulic lifting platform position is verified. The results show that the saturation current of the magnetorheological valve is 2.5 A. The addition of current to the magnetorheological valve leads to a rapid increase in both actuator speed and acceleration, which then levels off. Similarly, the response time of the actuator decreases with an increasing current until it stabilizes. At a coil current of 1.5 A, the actuator achieves a speed of approximately 86 mm s−1, an acceleration of approximately 105 mm s−2, and a response time of approximately 7.15 s. Furthermore, the lifting position accuracy of the hydraulic lifting platform is ±1 mm.

Hunting stability control of high-speed bogie based on active yaw damper

Hunting stability is an inherent property of railway vehicles that determines the operational speed. This paper establishes a half-vehicle model with nonlinear wheel/rail equivalent conicity and interactive forces. Additionally, the dynamic performances of vehicle under various levels of wheel wear with passive suspension are compared and analyzed. Importantly, the investigation delves into the hunting stability of the vehicle system, employing both linear and nonlinear control approaches. The results demonstrate a notable reduction in critical speed during the end-worn period with a passive suspension. However, this reduction can be substantially countered through the application of active control, resulting in a significant speed increase. The implementation of stiffness control raises the frequency of limit cycles, whereas damping control serves to diminish it. Notably, an appropriate linear cubic stiffness control effectively mitigates the amplitudes of limit cycles during instances of instability. Moreover, the control strategy derived from the simplified model is extended to enhance the stability of the entire vehicle system. The research findings hold the potential to offer a promising strategy for the active control of high-speed vehicles, particularly during periods of wheel wear.

Speed-dependent bacterial surface swimming.

In the early phase of biofilm formation, bacteria identify surfaces and increase the intracellular level of the second messenger c-di-GMP, resulting in a decrease in swimming speed. Here, we utilized advanced microscopy techniques to investigate the impact of swimming speed on bacterial surface swimming, focusing on Escherichia coli and Pseudomonas aeruginosa. We found that an increase in swimming speed led to an increase in the radius of curvature and a decrease in surface detention time. These effects were explained through hydrodynamic modeling as a result of an increase in the cell-surface distance with increasing swimming speed. We also observed distinct surface-escaping mechanisms between the two bacterial species. Our study suggests that a decrease in swimming speed could enhance the likelihood of cells adhering to the surface, promoting biofilm formation. This sheds light on the role of reduced swimming speed in the transition from motile to sedentary bacterial lifestyles.