Estimation of the kinetic energy dissipation in fall-arrest system and manikin during fall impact

Fall-arrest systems (FASs) have been widely applied to provide a safe stop during fall incidents for occupational activities. The mechanical interaction and kinetic energy exchange between the human body and the fall-arrest system during fall impact is one of the most important factors in FAS ergonomic design. In the current study, we developed a systematic approach to evaluate the energy dissipated in the energy absorbing lanyard (EAL) and in the harness/manikin during fall impact. The kinematics of the manikin and EAL during the impact were derived using the arrest-force time histories that were measured experimentally. We applied the proposed method to analyse the experimental data of drop tests at heights of 1.83 and 3.35 m. Our preliminary results indicate that approximately 84-92% of the kinetic energy is dissipated in the EAL system and the remainder is dissipated in the harness/manikin during fall impact. The proposed approach would be useful for the ergonomic design and performance evaluation of an FAS. STATEMENT OF RELEVANCE: Mechanical interaction, especially kinetic energy exchange, between the human body and the fall-arrest system during fall impact is one of the most important factors in the ergonomic design of a fall-arrest system. In the current study, we propose an approach to quantify the kinetic energy dissipated in the energy absorbing lanyard and in the harness/body system during fall impact.     

The impact of institutional forces on software metrics programs

Software metrics programs are an important part of a software organization's productivity and quality initiatives as precursors to process-based improvement programs. Like other innovative practices, the implementation of metrics programs is prone to influences from the greater institutional environment the organization exists in. In this paper, we study the influence of both external and internal institutional forces on the assimilation of metrics programs in software organizations. We use previous case-based research in software metrics programs as well as prior work in institutional theory in proposing a model of metrics implementation. The theoretical model is tested on data collected through a survey from 214 metrics managers in defense-related and commercial software organizations. Our results show that external institutions, such as customers and competitors, and internal institutions, such as managers, directly influence the extent to which organizations change their internal work-processes around metrics programs. Additionally, the adaptation of work-processes leads to increased use of metrics programs in decision-making within the organization. Our research informs managers about the importance of management support and institutions in metrics programs adaptation. In addition, managers may note that the continued use of metrics information in decision-making is contingent on adapting the organization's work-processes around the metrics program. Without these investments in metrics program adaptation, the true business value in implementing metrics and software process improvement is not realized.     

Estimation of compressive forces on lumbar spine from categorical posture data

To combine estimates of trunk posture and force into an integrated measure of load on the low back, continuous variables for body angles were estimated by assuming specified distributions within corresponding posture categories with Monte-Carlo (MC) simulation. The estimated posture angles were compared with reference measurements from the Lumbar Motion Monitor and inclinometers. The lumbar compression estimates, generated from simulated posture angles and from direct measurement, were compared. Trunk flexion showed high correlation between direct measurements and simulated angles, as did L5/S1 compression. The MC approach to extracting continuous posture angles from categorized observations did not appear to introduce large error in the variables used to estimate spinal compressive forces. When instrumentation methods of postural assessment are not feasible, a simulation approach combined with biomechanical modelling could be used to integrate multiple external exposure variables into estimates of compressive forces acting on the low back.     

Estimation of compressive forces on lumbar spine from categorical posture data

To combine estimates of trunk posture and force into an integrated measure of load on the low back, continuous variables for body angles were estimated by assuming specified distributions within corresponding posture categories with Monte-Carlo (MC) simulation. The estimated posture angles were compared with reference measurements from the Lumbar Motion Monitor and inclinometers. The lumbar compression estimates, generated from simulated posture angles and from direct measurement, were compared. Trunk flexion showed high correlation between direct measurements and simulated angles, as did L5/S1 compression. The MC approach to extracting continuous posture angles from categorized observations did not appear to introduce large error in the variables used to estimate spinal compressive forces. When instrumentation methods of postural assessment are not feasible, a simulation approach combined with biomechanical modelling could be used to integrate multiple external exposure variables into estimates of compressive forces acting on the low back.     

Estimation of excitation forces for wave energy converters control using pressure measurements

Most control algorithms of wave energy converters require prediction of wave elevation or excitation force for a short future horizon, to compute the control in an optimal sense. This paper presents an approach that requires the estimation of the excitation force and its derivatives at present time with no need for prediction. An extended Kalman filter is implemented to estimate the excitation force. The measurements in this approach are selected to be the pressures at discrete points on the buoy surface, in addition to the buoy heave position. The pressures on the buoy surface are more directly related to the excitation force on the buoy as opposed to wave elevation in front of the buoy. These pressure measurements are also more accurate and easier to obtain. A singular arc control is implemented to compute the steady-state control using the estimated excitation force. The estimated excitation force is expressed in the Laplace domain and substituted in the control, before the latter is transformed to the time domain. Numerical simulations are presented for a Bretschneider wave case study.     

Analysis of the demolding forces during hot embossing

Hot embossing is one of the main processing techniques for polymer microfabrication, which helps the LIGA (UV-LIGA) technology to achieve low cost mass production. When hot embossing of high aspect ratio microstructures, the deformation of microstructures usually occurs due to the demolding forces between the sidewall of mold inserts and the thermoplastic (PMMA). The study of the demolding process plays a key role in commercial manufacturing of polymer replicas. In this paper, the demolding behavior was analyzed by Finite element method using ABAQUS/Standard. Simulation identified the friction force caused by interface adhesion and thermal stress due to shrinkage between the mold and the polymer as the main sources of the demolding forces. Simulation also showed that the friction force made a greater contribution to the deformation than thermal stress, which is explained in the accompanying theoretical analysis. To minimize the friction force the optimized experiment was performed using PTFE (Teflon) as anti-adhesive films and using Ni-PTFE compound material mold inserts. Both lowered the surface adhesion energy and friction coefficient. Typical defects like pull-up and damaged edges can be reduced.     

Estimation of the dynamic spinal forces using a recurrent fuzzy neural network.

Estimation of the dynamic spinal forces from kinematics data is very complicated because it involves the handling of the relationship between kinematic variables and electromyography (EMG) signals, as well as the relationship between EMG signals and the forces. A recurrent fuzzy neural network (RFNN) model is proposed to establish the kinematics-EMG-force relationship and model the dynamics of muscular activities. The EMG signals are used as an intermediate output and are fed back to the input layer. Since EMG is a direct reflection of muscular activities, the feedback of this model has a physical meaning. It expresses the dynamics of muscular activities in a straightforward way and takes advantage from the recurrent property. The trained model can then have the forces predicted directly from kinematic variables while bypassing the costly procedure of measuring EMG signals and avoiding the use of a biomechanics model. A learning algorithm is derived for the RFNN model.     

Estimation of cutting forces and surface roughness for hard turning using neural networks

Metal cutting mechanics is quite complicated and it is very difficult to develop a comprehensive model which involves all cutting parameters affecting machining variables. In this study, machining variables such as cutting forces and surface roughness are measured during turning at different cutting parameters such as approaching angle, speed, feed and depth of cut. The data obtained by experimentation is analyzed and used to construct model using neural networks. The model obtained is then tested with the experimental data and results are indicated.     

Estimation of optimal feet forces and joint torques for on-line control of six-legged robot

The present study aims to estimate optimal feet forces and joint torques necessary for real-time control of a six-legged robot. Two approaches have been developed, such as minimization of norm of feet forces and minimization of norm of joint torques using the least squared method. Results of these two approaches have been compared with each other, and with those of available literature. As both of these approaches are found to be computationally fast, these are suitable for real-time control of the six-legged robot.     

Estimation of forces exerted by the fingers using standardised surface electromyography from the forearm

Determination and integration of human force capabilities and requirements is an essential component of ergonomic evaluation. With regard to hand-intensive tasks, direct force measurements can be cumbersome and intrusive. Here, the use of surface electromyography (EMG) was evaluated. EMG was obtained from three standardised electrode sites on the forearms of 30 individuals. Linear regression models were generated to estimate finger force levels from normalised electromyographic measures, while forces were generated in several finger couplings. The results suggest that standardised procedures for obtaining electromyographic data and simple linear models can be used to accurately estimate finger forces during a variety of finger exertions in fixed postures, although the level of accuracy depends on the type of model. Such models begin to overcome the limitations of direct finger strength measurements of individuals.     

Estimation of forces exerted by the fingers using standardised surface electromyography from the forearm

Determination and integration of human force capabilities and requirements is an essential component of ergonomic evaluation. With regard to hand-intensive tasks, direct force measurements can be cumbersome and intrusive. Here, the use of surface electromyography (EMG) was evaluated. EMG was obtained from three standardised electrode sites on the forearms of 30 individuals. Linear regression models were generated to estimate finger force levels from normalised electromyographic measures, while forces were generated in several finger couplings. The results suggest that standardised procedures for obtaining electromyographic data and simple linear models can be used to accurately estimate finger forces during a variety of finger exertions in fixed postures, although the level of accuracy depends on the type of model. Such models begin to overcome the limitations of direct finger strength measurements of individuals.     

Prediction of ground reaction forces and moments during sports-related movements

When performing inverse dynamic analysis (IDA) of musculoskeletal models to study human motion, inaccuracies in experimental input data and a mismatch between the model and subject lead to dynamic inconsistency. By predicting the ground reaction forces and moments (GRF&Ms) this inconsistency can be reduced and force plate measurements become unnecessary. In this study, a method for predicting GRF&Ms was validated for an array of sports-related movements. The method was applied to ten healthy subjects performing, for example, running, a side-cut manoeuvre, and vertical jump. Pearson’s correlation coefficient (\(r\)) and root-mean-square deviation were used to compare the predicted GRF&Ms and associated joint kinetics to the traditional IDA approach, where the GRF&Ms were measured using force plates. The main findings were that the method provided estimates comparable to traditional IDA across all movements for vertical GRFs (\(r\) ranging from 0.97 to 0.99, median 0.99), joint flexion moments (\(r\) ranging from 0.79 to 0.98, median 0.93), and resultant joint reaction forces (\(r\) ranging from 0.78 to 0.99, median 0.97). Considering these results, this method can be used instead of force plate measurements, hereby, facilitating IDA in sports science research and enabling complete IDA using motion analysis systems that do not incorporate force plate data.     

The impact of collinearity involving the intercept term on the numerical accuracy of regression

It is well known that multiple linear regression models with ill-conditioning can produce coefficient estimates with degraded numerical accuracy. This study examines the numerical accuracy of regression algorithms in the presence a particular type of ill-conditioning, that arising from collinear relationships that involve the intercept term and the independent variables. A benchmark data set is used to produce ill-conditioned data by introducing near linear relationships among the independent variables and the intercept term. The experiments reported here demonstrate that centering does not prevent a loss in numerical accuracy for this particular type of ill-conditioning. In addition, the ability of commonly used diagnostic checks to detect these problems is studied. As an example of the problems that arise from ignoring the relationships studied here we demonstrate that the regression procedures in two widely used statistical packages, SAS and SPSS-X, fail to detect this type of ill-conditioning and report highly inaccurate coefficient estimates.     

Effect of gloves on prehensile forces during lifting and holding tasks

The effect of gloves on the spatio-temporal characteristics of prehensile forces during lifting and holding tasks was investigated. Participants (n = 10) lifted a force transducer equipped object (weight = 0.29 N) with various types of gloves and barehanded using a two-fingered precision grip. Rubber surgical gloves of varied thicknesses (0.24, 0.61 and 1.02 mm) were worn to examine the effect of glove thickness on a rayon surface. It was found that grip force increased with thickness because the participants employed a higher safety margin above the minimum force required to hold the object. The safety margin for the barehanded condition was the smallest. The performance time for lifting the object was not influenced by the variation of glove thickness. The findings suggest that glove thickness, which presumably modifies the cutaneous sensation, influences grip force regulation. The effect of glove material (rubber and cotton) was also examined in relation to slippery (rayon) and non-slippery (sandpaper) surfaces. It was found that the participants used a larger grip force with the cotton glove than the rubber glove for the slippery surface, but not with the non-slippery surface. With use of the rubber glove, a relatively low grip force level was maintained for both slippery and non-slippery surfaces. The performance time for the cotton glove was longer than that for the rubber glove. The findings suggest that the rubber glove provides better efficiency of force and temporal control than the cotton glove in precision handling of small objects.     

The effect of the descent technique and truck cabin layout on the landing impact forces

The majority of injuries to truckers are caused by falls during the descent from the cab of the truck. Several studies have shown that the techniques used to descend from the truck and the layout of the truck's cabin are the principal cause of injury. The goal of the present study was to measure the effects of the descent techniques used by the trucker and the layout of the truck's cabin on the impact forces absorbed by the lower limbs and the back. Kinematic data, obtained with the aid of a video camera, were combined with the force platform data to allow for calculation of the lower limb and L₅–S₁ torques as well as L₅–S₁ compressive forces. The trucker descended from two different conventional tractor cabin layouts. Each trucker descended from cabin using either “facing the truck” (FT) or “back to the truck” (BT) techniques. The results demonstrate that the BT technique produces greater ground impact forces than the FT technique, particularly when the truck does not have a handrail. The BT technique also causes an increase in the compressive forces exerted on the back. In conclusion, the use of the FT technique along with the aids (i.e., handrails and all the steps) help lower the landing impact forces as well as the lumbosacral compressive forces.     

Estimation of distributions involving unobservable events: the case of optimal search with unknown Target Distributions

We consider the problem of estimating the parameters of a distribution when the underlying events are themselves unobservable. The aim of the exercise is to perform a task (for example, search a web-site or query a distributed database) based on a distribution involving the state of nature, except that we are not allowed to observe the various “states of nature” involved in this phenomenon. In particular, we concentrate on the task of searching for an object in a set of N locations (or bins) {C ₁, C ₂,…, C _N }, in which the probability of the object being in the location C _i is p _i , where P = [p ₁, p ₂,…, p _N ] ^T is called the Target Distribution. Also, the probability of locating the object in the bin within a specified time, given that it is in the bin, is given by a function called the Detection function, which, in its most common instantiation, is typically, specified by an exponential function. The intention is to allocate the available resources so as to maximize the probability of locating the object. The handicap, however, is that the time allowed is limited, and thus the fact that the object is not located in bin C _i within a specified time does not necessarily imply that the object is not in C _i . This problem has applications in searching large databases, distributed databases, and the world-wide web, where the location of the files sought for are unknown, and in developing various military and strategic policies. All of the research done in this area has assumed the knowledge of the {p _i }. In this paper we consider the problem of obtaining error bounds, estimating the Target Distribution, and allocating the search times when the {p _i } are unknown. To the best of our knowledge, these results are of a pioneering sort - they are the first available results in this area, and are particularly interesting because, as mentioned earlier, the events concerning the Target Distribution, in themselves, are unobservable.

Effects of body-borne equipment on occupant forces during a simulated helicopter crash

Helicopter seats are designed to a specified mass range including equipment and can only provide limited energy absorbing protection within its designed energy absorbing capability. Over recent years, military occupants have been required to carry increasing amounts of equipment, which may affect the probability of injury during a crash. To investigate the effects of increasing equipment mass during a helicopter crash on injury, a linear 7-degree-of-freedom mass–spring–damper model is developed to simulate an occupant wearing body-borne equipment on a crashworthy helicopter seat. A fixed load energy absorption mechanism is also included in the model. To examine the effects of equipment attachment types, the mass bodies representing the equipment are attached with a spring and damper, with low and high stiffness values indicating loose and tight attachment respectively. Dimensional analysis shows that the maximum forces are proportional to the initial impact velocity prior to stroke. The results demonstrate that increasing the equipment mass reduces the seat's capability to absorb the total impact energy at higher initial impact velocities. The safe velocity, the velocity that prevents bottoming out, reduces from 10.2 m/s, for an occupant without equipment, to 7.4 m/s for an occupant with an equipment mass of 40 kg at the lower and upper torso and 2 kg at the head. When the equipment mass is 40 kg at the hip and at the upper torso and 2 kg at the head, a maximum increase on the underside of the pelvis of 173% is measured, providing an increased possibility of injury in the lumbar region. Increases of 321%, 889% and 335% on the maximum forces on the hip, upper torso and head respectively create the potential for contact injury at the hip, upper torso and head from equipment and more than a 50% chance of spinal injury. The results show that increasing equipment mass significantly increases the potential for injury at the lumbar, hip, upper torso and head.