Development of a mathematical model for predicting electrically elicited quadriceps femoris muscle forces during isovelocity knee joint motion

<p>Abstract</p> <p>Background</p> <p>Direct electrical activation of skeletal muscles of patients with upper motor neuron lesions can restore functional movements, such as standing or walking. Because responses to electrical stimulation are highly nonlinear and time varying, accurate control of muscles to produce functional movements is very difficult. Accurate and predictive mathematical models can facilitate the design of stimulation patterns and control strategies that will produce the desired force and motion. In the present study, we build upon our previous isometric model to capture the effects of constant angular velocity on the forces produced during electrically elicited concentric contractions of healthy human quadriceps femoris muscle. Modelling the isovelocity condition is important because it will enable us to understand how our model behaves under the relatively simple condition of constant velocity and will enable us to better understand the interactions of muscle length, limb velocity, and stimulation pattern on the force produced by the muscle.</p> <p>Methods</p> <p>An additional term was introduced into our previous isometric model to predict the force responses during constant velocity limb motion. Ten healthy subjects were recruited for the study. Using a KinCom dynamometer, isometric and isovelocity force data were collected from the human quadriceps femoris muscle in response to a wide range of stimulation frequencies and patterns. % error, linear regression trend lines, and paired t-tests were used to test how well the model predicted the experimental forces. In addition, sensitivity analysis was performed using Fourier Amplitude Sensitivity Test to obtain a measure of the sensitivity of our model's output to changes in model parameters.</p> <p>Results</p> <p>Percentage RMS errors between modelled and experimental forces determined for each subject at each stimulation pattern and velocity showed that the errors were in general less than 20%. The coefficients of determination between the measured and predicted forces show that the model accounted for ~86% and ~85% of the variances in the measured force-time integrals and peak forces, respectively.</p> <p>Conclusion</p> <p>The range of predictive abilities of the isovelocity model in response to changes in muscle length, velocity, and stimulation frequency for each individual make it ideal for dynamic applications like FES cycling.</p

The role of an exergy-based building stock model for exploration of future decarbonisation scenarios and policy making

State-of-the-art research suggests that energy systems are best evaluated using exergy analysis, as exergy represents the real value of an energy source, demonstrating it to be the only rational basis for evaluation. After discovering the lack of thermodynamic integration into stock modelling, this paper presents the development of an exergy-based building stock model. The aim of this paper is twofold. Firstly, to investigate the impact of large-scale future energy retrofit scenarios in the English and Welsh (E&W) non-domestic sector, and secondly, to determine the potential of exergy analysis in improving sectoral efficiency and its potential implications on exergy-oriented policy making. The research explores seven different large-scale future retrofit scenarios that encompass typical, low-carbon, and low-exergy approaches. Modelling results show that by 2050, current regulations have the potential to reduce carbon emissions by up to 49.0±2.9% and increasing sector thermodynamic efficiency from 10.7% to 13.7%. On the other hand, a low-exergy oriented scenario based on renewable electricity and heat pumps is able to reduce carbon emissions by 88.2±2.4%, achieving a sectoral exergy efficiency of 19.8%. This modelling framework can provide energy policy makers with new insights on policy options based on exergy indicators and the assessment of their potential impact

An exergy-based multi-objective optimisation model for energy retrofit strategies in non-domestic buildings

While the building sector has a significant thermodynamic improvement potential, exergy analysis has been shown to provide new insight for the optimisation of building energy systems. This paper presents an exergy-based multi-objective optimisation tool that aims to assess the impact of a diverse range of retrofit measures with a focus on non-domestic buildings. EnergyPlus was used as a dynamic calculation engine for first law analysis, while a Python add-on was developed to link dynamic exergy analysis and a Genetic Algorithm optimisation process with the aforementioned software. Two UK archetype case studies (an office and a primary school) were used to test the feasibility of the proposed framework. Different measures combinations based on retrofitting the envelope insulation levels and the application of different HVAC configurations were assessed. The objective functions in this study are annual energy use, occupants' thermal comfort, and total building exergy destructions. A large range of optimal solutions was achieved highlighting the framework capabilities. The model achieved improvements of 53% in annual energy use, 51% of exergy destructions and 66% of thermal comfort for the school building, and 50%, 33%, and 80% for the office building. This approach can be extended by using exergoeconomic optimisation

Simlab Patches for Peace quilt block

Image created by ConText, LLC during Patches for Peace Quilt conservation project, 2011