Reduce Impact Forces Research Articles

Methods for Reducing Seed Damage in the Technological Process of Cotton Processing

The article describes the transfer of cotton to the next technological process while preserving its natural properties during the initial processing process. The analysis of methods of reducing impact forces when removing displaced stones with cotton is analyzed. For this, it is based on the primary processing of cotton.

Energy cost optimized dorsal leaf ankle-foot-orthoses reduce impact forces on the contralateral leg in people with unilateral plantar flexor weakness

BackgroundIn individuals with unilateral plantar flexor weakness, the second peak of the vertical ground reaction force (GRF) is decreased. This leads to a higher ground reaction force, e.g. impact, of the contralateral leg, potentially explaining quadriceps muscle and/or knee joint pain. Energy cost optimized dorsal leaf ankle-foot-orthoses (AFOs) may increase the push-off ground reaction force, which in turn could lead to lower impact forces on the contralateral leg. Research questions1) Are impact forces increased in the contralateral leg of people with unilateral plantar flexor weakness compared to healthy subjects? 2) Do energy cost optimized AFOs reduce impact forces and improve leg impact symmetry compared to walking without AFO in people with unilateral plantar flexor weakness? MethodsNine subjects with unilateral plantar flexor weakness were provided a dorsal leaf AFO with a stiffness primarily optimized for energy cost. Using 3D gait analyses peak vertical GRF during loading response with and without AFO, and the symmetry between the legs in peak GRF were calculated. Peak GRF and symmetry were compared with reference data of 23 healthy subjects. ResultsThe contralateral leg showed a significant higher peak vertical GRF (12.0 ± 0.9 vs 11.2 ± 0.6 N/kg, p = 0.005) compared to healthy reference data. When walking with AFO, the peak vertical GRF of the contralateral leg significantly reduced (from 12.0 ± 0.9 to 11.4 ± 0.7 N/kg, p = 0.017) and symmetry improved compared to no AFO (from 0.93 ± 0.06 to 1.01 ± 0.05, p < 0.001). ConclusionIn subjects with unilateral plantar flexor weakness, impact force on the contralateral leg was increased when compared to healthy subjects and dorsal leaf AFOs optimized for energy cost substantially reduced this force and improved impact symmetry when compared to walking without AFO. This indicates that dorsal leaf AFOs may reduce pain resulting from increased impact forces during gait in the contralateral leg in people with unilateral plantar flexor weakness.

Quick Setup of Force-Controlled Industrial Gluing Tasks Using Learning From Demonstration.

This paper presents a framework for programming in-contact tasks using learning by demonstration. The framework is demonstrated on an industrial gluing task, showing that a high quality robot behavior can be programmed using a single demonstration. A unified controller structure is proposed for the demonstration and execution of in-contact tasks that eases the transition from admittance controller for demonstration to parallel force/position control for the execution. The proposed controller is adapted according to the geometry of the task constraints, which is estimated online during the demonstration. In addition, the controller gains are adapted to the human behavior during demonstration to improve the quality of the demonstration. The considered gluing task requires the robot to alternate between free motion and in-contact motion; hence, an approach for minimizing contact forces during the switching between the two situations is presented. We evaluate our proposed system in a series of experiments, where we show that we are able to estimate the geometry of a curved surface, that our adaptive controller for demonstration allows users to achieve higher accuracy in a shorter demonstration duration when compared to an off-the-shelf controller for teaching implemented on a collaborative robot, and that our execution controller is able to reduce impact forces and apply a constant process force while adapting to the surface geometry.

Effects of acoustically paced cadence modulation on impact forces in running.

Increasing cadence in running has been advocated as a means to improve performance and reduce impact forces. Although acoustic pacing can be used for this purpose, it might by itself lead to an increased impact force, which would counteract the decrease in impact force that is being pursued by increasing the cadence with acoustic pacing and thus have a counterproductive effect. What are the effects of acoustic pacing and cadence on peak impact force and loading rate during running? Unpublished data from a previous study, in which 16 participants ran on an instrumented treadmill with various forms of acoustic pacing, were analyzed to address the research question. Peak impact force and loading rate while running with and without pacing, at three different cadences were extracted from the ground reaction force data and compared statistically between these two main conditions. In addition, we compared step-based and stride-based pacing, and paced and unpaced steps within stride-based pacing conditions. As expected, increasing the cadence was accompanied by a significant reduction in peak impact force and instantaneous vertical loading rate, whereas acoustic pacing had no significant effect on the impact forces compared to unpaced running with similar cadence, both before and after pacing. There were also no significant differences in this regard between step-based and stride-based pacing. Acoustic pacing does not adversely affect impact force when used to increase cadence in running with the aim of reducing the impact force and can thus be used for this purpose without introducing a counterproductive effect.

Mechanised Threshing of Pod Grains used as food and Strategies to Optimise the Technique: A Review

Pod grains threshing using mechanical devices is essential in understanding the diversities involved in the application of machine–crop parameter combinations towards achieving best quality grain. The integration of pod grains’ physical properties in optimizing product quality which is vital to meet the increasing global requirement is limited. However, with computing and technological advancements into thresher design and evaluation have been found to be capable of meeting these needs which are of interest to researchers. Over the past three–four decades, the applications of the technology in reducing impact force through modification of peg geometry have attracted researchers’ widespread interest and the future looks promising. This review presents an overview of mechanical thresher development and the applications in the field of pod grain production chain. The role of grain physical properties in threshers design, operations and with force sensors to reveal the mysteries surrounding the causes of grain damage and how they can be minimised are stressed. The current trends and future advances of such studies are also presented.

Impact force reduction by consecutive water entry of spheres

Abstract

Effects of a rebound shoe to reduce impact forces in jump-landing tasks

ObjectivesImpact forces are risk factors for injuries during jump-landing tasks. Rebound shoes could reduce impact forces and show potential applications in training and rehabilitation programs. Here, we determine the capacity of a rebound shoe in attenuating impact forces during different motor tasks involving foot landing. DesignCrossover laboratory research design. SettingsWomen not trained for jump-landing tasks performed different exercises while the vertical ground reaction force impact peak, time to peak, and asymmetries were determined. They were wearing a commercial rebound shoe and a control running shoe. Paired t-tests were used to compare the shoes and asymmetries. ParticipantsFifteen physically active women (average age of 23 years old, height of 1.64 m, and body mass of 63 kg). Main outcome measuresGround reaction forces. ResultsThe rebound shoe reduced the impact peak force and elicited slight asymmetries between the legs. The rebound shoe also showed a longer time to peak. ConclusionsThe rebound shoe tested reduced impact forces during jump-landing tasks, which is a potential application in training sessions and rehabilitation programs, requiring lower impact forces to the lower extremity. The effects of long-term use of these shoes still need to be investigated.

A Parametric Study of Compliant Link Design for Safe Physical Human–Robot Interaction

SUMMARYRobots of next-generation physically interact with the world rather than be caged in a controlled area, and they need to make contact with the open-ended environment to perform their task. Compliant robot links offer intrinsic mechanical compliance for addressing the safety issue for physical human–robot interactions (pHRI). However, many important research questions are yet to be answered. For instance, how do system parameters, for example, mechanical compliance, motor torque, impact velocities, and so on, affect the impact force? how to formulate system impact dynamics of compliant robots, and how to size their geometric dimensions to maximize impact force reduction. In this paper, we present a parametric study of compliant link (CL) design for safe pHRI. We first present a theoretical model of the pHRI system that is comprised of robot dynamics, an impact contact model, and dummy head dynamics. After experimentally validating the theoretical model, we then systematically study the effects of CL parameters on the impact force in more detail. Specifically, we explore how the design and actuation parameters affect the impact force of pHRI system. Based on the parametric studies of the CL design, we propose a step-by-step process and a list of concrete guidelines for designing CL with safety constraints in pHRI. We further conduct a simulation case study to validate this design process and design guidelines.

A novel steel damping system for rockfall protection galleries

A new steel damping device is proposed to achieve an effective solution for rockfall protection galleries. The system consists of an assembly of cold-formed steel crash boxes, namely Collapsible Tubular Element (CTE), with a transversal section and a length designed to assure, under axial loads, a compressive plastic deformation (folding) without the need of any guide means. Assembled in groups to create a modular cushion, the system reduces the deceleration and the derived impact force due to an impacting block mass during a rockfall event. The influence of both the system module configuration (number of CTEs, presence of restraining cables) and the boulder parameters (mass, angle, and velocity at the impact) is investigated, and a Dynamic Finite Element analyses, along with a full-scale experimental test, have been carried out to evaluate the system performances. The obtained results indicate how the proposed system mitigates the dynamic amplification of the forces transmitted from the impact point to the roof slab, with a mean value of the impact force increased by only 2% within the damping cushion, showing, if compared with the mainly adopted damping cushion systems, a drastic reduction of both impact force and dead load on the gallery's roof. Finally, due to its dimensional stability, the proposed damping device is not affected by compaction over time and by the consequent increase of the impact force.

DeepImpact: a deep learning model for whole body vibration control using impact force monitoring

Large capacity shovels are matched with large capacity dump trucks for gaining economic advantage in surface mining operations. These high impact shovel loading operations (HISLO) result in large dynamic impact force at truck bed surface. This impact force generates high-frequency shockwaves which expose the operator to whole body vibrations (WBVs). These WBVs cause serious injuries and fatalities to operators in mining operations. The present work focuses on developing solution technology for minimizing impact force on truck bed surface, which is the cause of these WBVs. The proposed technology involves modifying the truck bed structural design through the addition of synthetic rubber. Detailed experiments, with the technology implementation, showed a reduction of impact force by 22.60% and 23.83%, during the first and second shovel passes, respectively, which in turn reduced the WBV levels by 25.56% and 26.95% during the first and second shovel passes, respectively, at the operator’s seat. To make the smart implementation of the technology feasible, a novel state-of-the-art deep learning model, ‘DeepImpact,’ is designed and developed for impact force real-time monitoring during a HISLO operation. DeepImpact showed an exceptional performance, giving an R2, RMSE, and MAE values of 0.9948, 10.750, and 6.33, respectively, during the model validation. This smart and intelligent real-time monitoring system with design and process optimization would minimize the impact force on truck surface, which in turn would reduce the level of vibration on the operator, thus leading to a safer and healthier working environment at mining sites.

A comparison of floor surfaces for injury prevention in care settings: impact forces and horizontal pulling force required to move wheeled equipment.

Severe falls often occur in hospitals and care homes. Shock-absorbing flooring is one potential solution to prevent fall-related injuries; however, no standards exist for characterizing flooring as an injury prevention measure. Shock-absorbing flooring use in high-risk settings may influence both patients (injury-saving potential) and staff (manoeuvring equipment). We aimed to explore two tests to characterize floors, to determine shock absorbency and horizontal pulling force required to move wheeled objects. Mechanical testing was performed according to the Canadian Standards Association Z325 Hip Protectors document. This test was developed for hip protectors but is applicable to compliant surfaces that form part of the floor. Tests were performed on commercially available floor materials (suitable for care settings) to assess the force required to initiate movement of a wheeled object across the floor. We explored the relationships between horizontal force required to pull wheeled objects, impact force, floor thickness, and core material. Considerable differences were identified between floor samples in their ability to reduce the peak impact force (range 0.7-25%). A peak force reduction of up to 25% can be achieved with a specially designed rubber underlay. Horizontal pulling force increased with floor thickness but was lower for rubber floors. There was no direct relationship between impact attenuation and horizontal pulling force. Whilst thickness and core material explain some variations (66.5% for wheel movement; 82.3% for impact), other unmeasured factors clearly influence floor performance. These results can inform the development of flooring and the establishment of standards needed to underpin practice, research, and development in this field.

Toward Tradeoff Between Impact Force Reduction and Maximum Safe Speed: Dynamic Parameter Optimization of Variable Stiffness Robots

Abstract Variable stiffness robots may provide an effective way of trading-off between safety and speed during physical human–robot interaction. In such a compromise, the impact force reduction capability and maximum safe speed are two key performance measures. To quantitatively study how dynamic parameters such as mass, inertia, and stiffness affect these two performance measures, performance indices for impact force reduction capability and maximum speed of variable stiffness robots are proposed based on the impact ellipsoid in this paper. The proposed performance indices consider different impact directions and kinematic configurations in the large. Combining the two performance indices, the global performance of variable stiffness robots is defined. A two-step optimization method is designed to achieve this global performance. A two-link variable stiffness link robot example is provided to show the efficacy of the proposed method.

A Comparative Study on the Effect of Mechanical Compliance for a Safe Physical Human–Robot Interaction

Abstract In this paper, we study the effects of mechanical compliance on safety in physical human–robot interaction (pHRI). More specifically, we compare the effect of joint compliance and link compliance on the impact force assuming a contact occurred between a robot and a human head. We first establish pHRI system models that are composed of robot dynamics, an impact contact model, and head dynamics. These models are validated by Simscape simulation. By comparing impact results with a robotic arm made of a compliant link (CL) and compliant joint (CJ), we conclude that the CL design produces a smaller maximum impact force given the same lateral stiffness as well as other physical and geometric parameters. Furthermore, we compare the variable stiffness joint (VSJ) with the variable stiffness link (VSL) for various actuation parameters and design parameters. While decreasing stiffness of CJs cannot effectively reduce the maximum impact force, CL design is more effective in reducing impact force by varying the link stiffness. We conclude that the CL design potentially outperforms the CJ design in addressing safety in pHRI and can be used as a promising alternative solution to address the safety constraints in pHRI.

Reduction of impact force and stress during high-speed operation based on hybrid control of positioning and force for injection molding machine

Reduction of impact force and stress during high-speed operation based on hybrid control of positioning and force for injection molding machine

Developing Fall-impact Protection Pad with 3D Mesh Curved Surface Structure using 3D Printing Technology.

In this study, we present the development of fall-impact protection pads for elderly people using three-dimensional (3D) printing technology. To develop fall-impact protection clothing, it is important to maintain the functionality of the protection pad while ensuring that its effectiveness and appearance remain optimal in the process of inserting it. Therefore, this study explores the benefit of exploiting 3D scan data of the human body using 3D printing technology to develop a fall-impact protection pad that is highly suited to the human body shape. The purpose of this study was to present a 3D modeling process for creating curved protective pads comprising a hexagonal mesh with a spacer fabric structure and to verify the impact protection performance by printing curved pads. To this end, we set up a section that includes pads in the 3D human body scan data and extracted body surface information to be applied in the generation of the pad surface. The sheet-shaped hexagonal mesh structure was cut and separated according to the pad outline, and then deformed according to the curved surface of the human body. The pads were printed, and their protection performance was evaluated; a 79.2–81.8% reduction in impact force was observed compared to similar cases in which the pads were not used.

Transition to forefoot strike reduces load rates more effectively than altered cadence

BackgroundExcessive vertical impacts at landing are associated with common running injuries. Two primary gait-retraining interventions aimed at reducing impact forces are transition to forefoot strike and increasing cadence. The objective of this study was to compare the short- and long-term effects of 2 gait-retraining interventions aimed at reducing landing impacts. MethodsA total of 39 healthy recreational runners using a rearfoot strike and a cadence of ≤170 steps/min were randomized into cadence (CAD) or forefoot strike (FFS) groups. All participants performed 4 weeks of strengthening followed by 8 sessions of gait-retraining using auditory feedback. Vertical average load rates (VALR) and vertical instantaneous load rates (VILR) were calculated from the vertical ground reaction force curve. Both cadence and foot strike angle were measured using 3D motion analysis and an instrumented treadmill at baseline and at 1 week, 1 month, and 6 months post retraining. ResultsANOVA revealed that the FFS group had significant reductions in VALR (49.7%) and VILR (41.7%), and changes were maintained long term. Foot strike angle in the FFS group changed from 14.2° dorsiflexion at baseline to 3.4° plantarflexion, with changes maintained long term. The CAD group exhibited significant reduction only in VALR (16%) and only at 6 months. Both groups had significant and similar increases in cadence at all follow-ups (CAD, +7.2% to 173 steps/min; and FFS, +6.1% to 172 steps/min). ConclusionForefoot strike gait-retraining resulted in significantly greater reductions in VALR and similar increases in cadence compared to cadence gait-retraining in the short and long term. Cadence gait-retraining resulted in small reductions in VALR at only the 6-month follow-up.

Direct numerical simulation study of droplet spreading on spherical particles

Direct Numerical Simulations have been performed to study the droplet spreading behaviour on a spherical surface. A coupled immersed boundary and volume of fluid method is used to represent the gas-liquid-solid interactions. The contact area of the droplet on the surface is recorded in order to fit the initial spreading with a power-law representation, using the contact-angle and interface curvature as fitting parameters. Small viscous droplets are used to reduce interfacial oscillations as well as low drop velocities to reduce impact forces. A decrease of spreading area with increasing curvature is observed. Moreover, the model shows good agreement compared to equilibrium states. A strong contact-angle dependence is found for the pre-factor of the power law, which is expected, and a linear decrease was found in the exponent for increasing curvature of the surface.

Effect of bed roughness on tsunami-like waves and induced loads on buildings

Tsunami, impulse-waves and dam-break waves afflict humanity with casualties and damages. An insight into the flow mechanisms of these waves is important to provide safety and reduce reconstruction costs. This experimental study focuses on the effect of bed roughness on the main hydrodynamic properties of surges propagating on dry bed. In addition, the resulting wave impact forces on buildings with and without openings are studied. Results pointed out that dry bed surges on a rough bed had a lower front celerity and a higher flow depth, resulting into inundation depths during the impact around 20% higher as compared to the smooth bed. Furthermore, a rough bed induced a lower momentum flux during wave propagation, resulting into lower impact forces exerted on the building. The rough bed configuration also caused shorter impact durations, leading to lower impulse values transferred to the building. Results pointed out that even on rough bed, openings within the buildings linearly reduced impact forces, thus providing some helpful information for the design of safer coastal structures.

A design methodology based on full dynamic model for magnetorheological energy absorber equipped with disc springs

The spring of magnetorheological energy absorber (MREA) is an indispensable component that provides a restoring force for the piston back to the initial position. To reduce impact force, the stroke of a typical MREA is usually sacrificed (i.e., extended stroke and prolonged buffer time). In some situations, however, a fast return of piston is required and the impact load is huge. It is difficult for conventional coil/gas springs to qualify due to the limitations in obtaining high stiffness. In this study, we employ the disc spring as a rebound element for MREA because of its feature in providing large force within narrow deformation. Optimal designs are significant for improving the MREA performance, but most of them have been developed based on the quasi-static model that ignores inertia effect. However, the inertia effect becomes an important role in dynamic behavior under high-speed impacts. Most recently, we proposed a full dynamic model considering inertia effect by using the non-averaged acceleration. As a further step, this study presents a design methodology based on this full dynamic model for an MREA with disc spring. The design objective is to identify the geometric dimensions of disc spring and MR valve to return the piston back to its initial position as fast as possible after a fast impact loading. The design flowcharts for disc spring and MR valve are presented. The load-deflection relationship of disc spring is obtained based on Almen–Laszlo theory. The magnetic field intensity in the MR gap is analyzed by using Kirchhoff’s law and the magnetic flux conversation rule. Two identical MREAs are fabricated and tested via a high-speed drop tower system. The effectiveness of the design methodology is validated by a comparison of MREA behaviors between the tests and full dynamic modeling.

Application of artificial neural networks to map the mechanical response of a thermoplastic elastomer

Thermoplastic elastomers are materials widely used in engineering applications due to their excellent performance to absorb mechanical vibrations and to reduce impact forces. However, their mechanical response is non-linear, which prevents linear models from predicting stresses reliably in the design and analyses of mechanical parts. This study presents a feedforward artificial neural network that was trained with stress/strain data of a thermoplastic elastomer. Such data come from a database specialized in materials from which ten curves were obtained to train and to develop an artificial neural network model. Additionally, five hyperelastic models and two probabilistic neural networks were used and compared to the proposed model. The simulation results show that the feedforward artificial neural network model is the most accurate to predict the non-linear thermoplastic elastomer response because it presented a coefficient of determination (R2) of 0.996 0 and differences of 1% with respect to the experimental data. The artificial neural network model also served to map the stress response for a temperature range between −20 °C to 160 °C for the thermoplastic elastomer material. On this basis, the presented feedforward neural network approach was tested by predicting the response of seven additional thermoplastic elastomers. The results showed that such an approach can attain thermoplastic elastomers responses with differences of 4% respect to experimental data. Consequently, the proposed approach simplifies the prediction of stress/strain curves for thermoplastic elastomer materials.