Suraj Jaiswal

The objective of this paper is to explore methodologies used to estimate the mechanical cost of locomotion and evaluate their validity as indicators of metabolic cost within rehabilitation contexts. Aging societies face rising healthcare costs and fewer workers. Remote monitoring of rehabilitation progress may help address these challenges. Because locomotion mechanics are easier to measure than metabolic cost, understanding whether mechanical cost of transport can serve as a surrogate is of interest. We conducted a systematic search for studies on mechanical work or power and metabolic energy consumption in adults under physical rehabilitation contexts. Abstract, full text screening, and data extraction were performed. Ten articles were included. We found no direct relationship between mechanical cost and metabolic cost in the included studies. However, consistent trends were observed: interventions that provided net positive work generally reduced both mechanical and metabolic costs. Similar trends were found in wheelchair propulsion, where mechanical advantage and power assistance reduced both mechanical cost and metabolic demand for wheelchair users. Rehabilitation progress can be monitored using metabolic cost, and given the observed parallel trends, mechanical cost may also serve as a practical indicator, although further research is needed to establish its validity as a surrogate.

Mechanical systems are extensively utilized in many fields such as the forest, earth-moving, and mining industries. The computer simulation of a mechanical system is often carried out by utilizing a multibody dynamics approach, where various semi-recursive methods can lead to varied computational efficiencies. The objective of this paper is to introduce and systematically compare various semi-recursive multibody methods based on different reference frames in the framework of the index-3 augmented Lagrangian method with projections. The novelty of this paper is the direct formulation and implementation of the method in the center of mass reference frame, whereas the method in the instantaneous reference frame is taken from the literature. Here, simulation models of four-bar, slider-crank, and quick-return mechanical structures are demonstrated as numerical examples. The methods are analyzed depending on the simulation accuracy, violation of constraints, mechanical energy balance, and computational efficiency. The results show that for the presented examples, the center of mass reference frame method is computationally efficient and accurate compared to the method taken from the literature.

Heavy machinery has evolved significantly in productivity, efficiency, and safety over the past century and a half, where most technological advances occurred after the 1990s. The field of multibody dynamics has significantly contributed to this development. The objective of this study is to introduce the historical evolution of heavy machinery and to analyze the general role of multibody dynamics in this evolution. The latter part of the objective is the novel contribution of this study. The historical evolution of heavy machinery is presented from the ancient times of 30–20 BC to the modern innovations of 2024. The general role of multibody dynamics in heavy machinery is identified and analyzed in five phases, from using simple kinematic models in the 1970s to real-time simulations and autonomous systems in the 2020s. This study can serve as a benchmark for future work.

Multibody simulation of heavy machinery such as excavators, wheel loaders, and tractors is highly influenced by parameters of hydraulic components such as the control valves. The objective of this study is to introduce gamification to parameterize the flow characteristics of control valves in real-time multibody simulation of an excavator. To this end, the mechanics of the excavator is modeled using a semirecursive multibody method and the hydraulics is modeled using the lumped fluid method. The gamification concept is introduced using game elements and game-design techniques in a nongame context. Using the excavator case example, various tests with increasing level of difficulty are performed on a simulator. The results of this study exhibit the utility of such a gamified simulation model in various phases of user training and product development.

Medieval combat sport is a form of mixed martial art in which combatants engage in fighting using offensive and defensive equipment while dressed in full armor. The sport is considered extremely taxing, making it nearly impossible to maintain the same level of performance. However, this form of sport has not been thoroughly analyzed, and its impact on human physical response is largely unknown. To address this gap, the study reported here aimed to introduce and test a procedure for analyzing human physical responses within the framework of the sport. To accomplish this, two experienced combatants were asked to engage in a series of strikes, performed in the form of a set duel simulating a professional fight competition. The kinematic aspect of the procedure was examined using motion analysis with the help of an IMU suit, while the physiological aspect was evaluated based on blood lactate levels and heart rate measurements. Furthermore, an ergometer test conducted in a laboratory setting aimed to determine the lactate threshold. The duel results showed noticeable decreases in the kinematic aspects of the strikes, such as the velocity of impact, and a dramatic rise in physiological aspects, such as heart rate and blood lactate levels. During the duel sets, the blood lactate surpassed the threshold level, and at the end, the heart rate exceeded the maximum age-related level. Practicing medieval combat sport has been shown to impose an extreme physical load on the bodies of combatants, noticeably affecting their performance levels.

Automatization of hydraulic machinery requires accurate information of the current dynamic state of the machinery but also information of the underlying dynamic model characterized by a set of parameters. Some of the parameters can be considered static and well defined, such as machinery dimensions, whereas a part of the parameter set is time varying and needs to be identified based on observations. Particularly, difficult parameters to estimate are the ones, from which no prior knowledge is available. Consequently, the parameter corrections cannot be assumed to be small, which is commonly required for the existing parameter estimation algorithms. This study creates an online capable identification algorithm for estimation of a load mass operated by a hydraulic crane. In the case of load mass estimation, the unknown parameter can be practically any positive value, which implies the parameter corrections to be large. In this study, the estimation problem is divided in two parts: First, the dynamical states of the system are estimated based on the system kinematic relationships and dynamics of the hydraulic circuit. Secondly, the unknown load mass is estimated based on the known hydraulic forces and kinematics using the inverse dynamics of the mechanical structure. The proposed algorithm is tested with both artificially created measurements and with an experimental setup. The results show that both the kinematics of the structure and hydraulic pressures can be accurately estimated using the proposed method. Moreover, the method can be used to further estimate the payload mass. A drawback related to inverse dynamics is that it produces biased estimates in static equilibrium because of the discontinuous nature of static friction force. However, this drawback can be avoided, in part, by not updating the payload estimate in the low-velocity region. The proposed estimation methodology is capable for online identification, and as such, it can be used to adapt the control laws of automated machinery. Moreover, the methodology can be useful to record and document the amount of payload being handled during a work cycle.