Publikationen

Zusammenfassung

Stroke is one of the leading causes of adult disability affecting millions of people worldwide. Post-stroke cognitive and motor impairments diminish quality of life and functional independence. There is an increased risk of having a second stroke and developing secondary conditions with long-term social and economic impacts. With increasing number of stroke incidents, shortage of medical professionals and limited budgets, health services are struggling to provide a care that can break the vicious cycle of stroke. Effective post-stroke recovery hinges on holistic, integrative and personalized care starting from improved diagnosis and treatment in clinics to continuous rehabilitation and support in the community. To improve stroke care pathways, there have been growing efforts in discovering biomarkers that can provide valuable insights into the neural, physiological and biomechanical consequences of stroke and how patients respond to new interventions. In this review paper, we aim to summarize recent biomarker discovery research focusing on three modalities (brain imaging, blood sampling and gait assessments), look at some established and forthcoming biomarkers, and discuss their usefulness and complementarity within the context of comprehensive stroke care. We also emphasize the importance of biomarker guided personalized interventions to enhance stroke treatment and post-stroke recovery.

Zusammenfassung

Metabolic zonation refers to the spatial separation of metabolic functions along the sinusoidal axes of the liver. This phenomenon forms the foundation for adjusting hepatic metabolism to physiological requirements in health and disease (e.g., metabolic dysfunction-associated steatotic liver disease/MASLD). Zonated metabolic functions are influenced by zonal morphological abnormalities in the liver, such as periportal fibrosis and pericentral steatosis. We aim to analyze the interplay between microperfusion, oxygen gradient, fat metabolism and resulting zonated fat accumulation in a liver lobule. Therefore we developed a continuum biomechanical, tri-phasic, bi-scale, and multicomponent in silico model, which allows to numerically simulate coupled perfusion-function-growth interactions two-dimensionally in liver lobules. The developed homogenized model has the following specifications: (i) thermodynamically consistent, (ii) tri-phase model (tissue, fat, blood), (iii) penta-substances (glycogen, glucose, lactate, FFA, and oxygen), and (iv) bi-scale approach (lobule, cell). Our presented in silico model accounts for the mutual coupling between spatial and time-dependent liver perfusion, metabolic pathways and fat accumulation. The model thus allows the prediction of fat development in the liver lobule, depending on perfusion, oxygen and plasma concentration of free fatty acids (FFA), oxidative processes, the synthesis and the secretion of triglycerides (TGs). The use of a bi-scale approach allows in addition to focus on scale bridging processes. Thus, we will investigate how changes at the cellular scale affect perfusion at the lobular scale and vice versa. This allows to predict the zonation of fat distribution (periportal or pericentral) depending on initial conditions, as well as external and internal boundary value conditions.

Zusammenfassung

To maximize the usefulness of groundwater flow models for the protection of aquifers and abstraction wells, it is necessary to identify and decrease the uncertainty associated with the major parameters such as permeability. To do this, there is a need to develop set of estimates representing subsurface heterogeneity or representative soil permeability estimates. Here, we use a coupled Random Field and extended Theory of Porous Media (eTPM) simulation to develop a robust model with a good predictive ability that reduces uncertainty. The coupled model is then validated with a physical sandbox experiment. Uncertainty is reduced by using 500 realisations of the permeability parameter using the eTPM approach. A multi-layer contaminant transport scenario with varying permeabilities, similar to what could be expected with shallow alluvial sediments, is simulated. The results show that the contaminant arrival time could be strongly affected by random field realizations of permeability compared with a modelled homogenous permeability parameter. The breakthrough time for heterogeneous permeabilities is shorter than the homogeneous condition. Using the 75% confidence interval (CI), the average contaminant concentration shows 4.4% variation from the average values of the considered area and 8.9% variation in the case of a 95% confidence interval.

Zusammenfassung

In this paper, the thermal behavior of living tissue has been modeled using a non-local three-phase lag approach. The simulation results of this model- ing have been compared with experimental results of alternating radiation with different periods on human skin, yielding satisfactory alignments. Ad- ditionally, it has been investigated that the TPL model, which is an equation with an integral term, can simulate energy accumulation within the dermal tissue. Moreover, the non-local nature of the modeling has been explored to alter the influence of phase lag terms. Furthermore, apart from numer- ically solving the equation, an analytical solution has been derived for the frequency equation, demonstrating the effects of simulation parameters on the frequency equation and simulation results. The obtained results indi cate that these parameters not only independently affect the outcomes but also interact with other parameters, leading to variations beyond their direct impacts.

Zusammenfassung

Physics-informed neural networks~(PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks~(AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the Formula: see text relative error by Formula: see text after 25,000 epochs for a one-dimensional consolidation problem based on Biot's theory, and an average improvement by Formula: see text with a transfer approach to the theory of porous media.

Zusammenfassung

Aging leads to a decline in muscle mass and force-generating capacity. Ultrasound shear wave elastography (SWE) is a non-invasive method to capture age-related muscular adaptation. This study assessed biceps brachii muscle (BB) mechanics, hypothesizing that shear elastic modulus reflects (i) passive muscle force increase imposed by length change, (ii) activation-dependent mechanical changes, and (iii) differences between older and younger individuals. Fourteen healthy volunteers aged 60--80 participated. Shear elastic modulus, surface electromyography, and elbow torque were measured at five elbow positions in passive and active states. Data collected from young adults aged 20--40 were compared. The BB passive shear elastic modulus increased from flexion to extension, with the older group exhibiting up to 52.58\% higher values. Maximum elbow flexion torque decreased in extended positions, with the older group 23.67\% weaker. Significant effects of elbow angle, activity level, and age on total and active shear elastic modulus were found during submaximal contractions. The older group had 20.25\% lower active shear elastic modulus at 25\% maximum voluntary contraction. SWE effectively quantified passive and activation-dependent BB mechanics, detecting age-related alterations at rest and during low-level activities. These findings suggest shear elastic modulus as a promising biomarker for identifying altered muscle mechanics in aging.

Zusammenfassung

Physics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks (AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the L2 relative error by 64.84% after 25,000 epochs for a one-dimensional consolidation problem based on Biot’s theory, and an average improvement by 58.80% with a transfer approach to the theory of porous media.

Zusammenfassung

Myasthenia gravis (MG) is often accompanied with muscle weakness; however, little is known about mechanical adaptions of the affected muscles. As the latter can be assessed using ultrasound shear wave elastography (SWE), this study characterizes the biceps brachii muscle of 11 patients with MG and compares them with that of 14 healthy volunteers. Simultaneous SWE, elbow torque and surface electromyography measurements were performed during rest, maximal voluntary contraction (MVC) and submaximal isometric contractions (up to 25%, 50% and 75% MVC) at different elbow angles from flexion to extension. We found that, with increasing elbow angle, maximum elbow torque decreased (p < 0.001), whereas muscle stiffness increased during rest (p = 0.001), MVC (p = 0.004) and submaximal contractions (p < 0.001). Muscle stiffness increased with increasing contraction intensities during submaximal contractions (p < 0.001). In comparison to the healthy cohort, muscle stiffness of MG patients was 2.1 times higher at rest (p < 0.001) but 8.93% lower in active state (75% MVC, p = 0.044). We conclude that (i) increased muscle stiffness shown by SWE during rest might be an indicator of MG, (ii) SWE reflects muscle weakness and (iii) SWE can be used to characterize MG muscle.

Zusammenfassung

Mechanical characterization of individual muscles in their in vivo environment is not well studied. Shear wave elastography (SWE) as a non-invasive technique was shown to be promising in quantifying the local mechanical properties of skeletal muscles. This study aimed to investigate the mechanics of the biceps brachii muscle (BB) derived from SWE in relation to elbow joint position and contraction intensity during isometric contraction. 14 healthy, young subjects participated in the study and five different joint positions (60°–180° elbow angle) were investigated. Shear elastic modulus and surface electromyography (sEMG) of the BB and elbow torque were measured simultaneously, both in passive (i.e., resting) and active states during slow, sub-maximal isometric ramp contractions up to 25%, 50%, and 75% of the maximum voluntary contraction. At passive state, the shear elastic modulus of the BB increased with increasing elbow angle (p < 0.001). Maximum elbow flexion torque was produced at 60° and it decreased with increasing elbow angle (p = 0.001). During sub-maximal contractions, both elbow angle (p < 0.001) and contraction intensity (p < 0.001) had significant effects on the shear elastic modulus but only contraction intensity (p < 0.001) affected sEMG amplitude of the BB. Although torque was decreased at extended elbow positions (150°, 180°), higher active shear elastic modulus of BB muscle was found compared to flexed positions (60°, 90°). Linear regression of the BB sEMG amplitude over elbow torque showed good agreement for all joint positions (R2 between 0.69 and 0.89) while the linear agreement between shear elastic modulus of BB and elbow torque differed between flexed (R2 = 0.70 at 60° and R2 = 0.79 at 90°) and extended positions (with the lowest R2 = 0.57 at 150°). We conclude that using SWE, we can detect length-dependent mechanical changes of BB both in passive and active states. More importantly, SWE can be used to characterize active muscle properties in vivo. The present findings have critical importance for developing muscle stiffness as a measure of individual muscle force to validate muscle models and using SWE in clinical diagnostics.

Zusammenfassung

This paper investigates temperature and vibration responses of human multi-layer skin tissue to laser irradiation. Due to the viscoelastic property of skin, a standard linear solid model known as the Zener model with two relaxation times with dual phase-lag heat conduction model has been used to describe the temperature and displacement in a one-dimensional form. The obtained differential equations have been discretized in the weak form to balance thermal and vibrational energies. The extracted time-dependent ordinary differential equations have been solved numerically by integration over time. The investigations are based on the effect of four relaxation times of temperature, heat, strain, and stress with laser effect in the form of a single step or repeated pulses on the behavior of the skin. By examining their results, the effect of phase lags has also been discussed, showing that the heat phase lag has a complex impact on thermal response and depends on the type of laser radiation. The phase lag of temperature reduces the temperature change rate, and the strain phase lag spreads the displacement at later times, gives inertia to the system, and dampens the system's vibration.

Zusammenfassung

This study reviews the relationship between muscle-tendon biomechanics and joint function, with a particular focus on how cerebral palsy (CP) affects this relationship. In healthy individuals, muscle size is a critical determinant of strength, with muscle volume, cross-sectional area, and moment arm correlating with knee and ankle joint torque for different isometric/isokinetic contractions. However, in CP, impaired muscle growth contributes to joint pathophysiology even though only a limited number of studies have investigated the impact of deficits in muscle size on pathological joint function. As muscles are the primary factors determining joint torque, in this review two main approaches used for muscle force quantification are discussed. The direct quantification of individual muscle forces from their relevant tendons through intraoperative approaches holds a high potential for characterizing healthy and diseased muscles but poses challenges due to the invasive nature of the technique. On the other hand, musculoskeletal models, using an inverse dynamic approach, can predict muscle forces, but rely on several assumptions and have inherent limitations. Neither technique has become established in routine clinical practice. Nevertheless, identifying the relative contribution of each muscle to the overall joint moment would be key for diagnosis and formulating efficient treatment strategies for patients with CP. This review emphasizes the necessity of implementing the intraoperative approach into general surgical practice, particularly for joint correction operations in diverse patient groups. Obtaining in vivo data directly would enhance musculoskeletal models, providing more accurate force estimations. This integrated approach can improve the clinicians’ decision-making process and advance treatment strategies by predicting changes at the muscle and joint levels before interventions, thus, holding the potential to significantly enhance clinical outcomes.

Zusammenfassung

Glaucoma as an eye disease influences the optic nerve, resulting in progressive vision loss and, thus, blindness. For this disease, the most important risk factor is high intraocular pressure. Therefore, it is important to accurately measure the intraocular pressure. The present work aimes to present a mathematical description of a capacitive pressure sensor based on a Micro-Electro-Mechanical-Systems (MEMS) to measure intraocular pressure (IOP). The relatively high working bias voltage of MEMS capacitive pressure sensors restricts their potential applications as implantable sensors. Hence, Polydimethylsiloxane (PDMS) is employed as a porous elastomeric substance between the deformable and fixed electrodes of the capacitor. With a low young modulus and a higher dielectric constant, it reduces the sensor's working bias voltage. The PDMS's permittivity and young modulus are a function of the porosity volume fraction based on displacement in terms of a power law with fractional power constant. The dynamic equation of the microplate's transversal motion is used in the developed model, taking mid-plane stre-tching into account along with the generated force owing to the PDMS film squeezing. To decompose the governing nonlinear equation, a weak formulation is used with appropriate basis functions, thus integrating the attained ordinary differential equations over time. The sensor response to static pressure and step-wise alteration of the applied pressure is examined by dynamic and static analysis. The results of pull-in voltage reveal that using the PDMS as a dielectric causes a considerable reduction. Additionally, the effect of the PDMS elasticity on the capacitance and displacement was assessed along with the effects of the geometrical parameters on the sensor response.

Zusammenfassung

The outcome of vertebroplasty is hard to predict due to its dependence on complex factors like bone cement and marrow rheologies. Cement leakage could occur if the procedure is done incorrectly, potentially causing adverse complications. A reliable simulation could predict the patient-specific outcome preoperatively and avoid the risk of cement leakage. Therefore, the aim of this work was to introduce a computationally feasible and experimentally validated model for simulating vertebroplasty. The developed model is a multiphase continuum-mechanical macro-scale model based on the Theory of Porous Media. The related governing equations were discretized using a combined finite element–finite volume approach by the so-called Box discretization. Three different rheological upscaling methods were used to compare and determine the most suitable approach for this application. For validation, a benchmark experiment was set up and simulated using the model. The influence of bone marrow and parameters like permeability, porosity, etc., was investigated to study the effect of varying conditions on vertebroplasty. The presented model could realistically simulate the injection of bone cement in porous materials when used with the correct rheological upscaling models, of which the semi-analytical averaging of the viscosity gave the best results. The marrow viscosity is identified as the crucial reference to categorize bone cements as ‘high- ’or ‘low-’ viscosity in the context of vertebroplasty. It is confirmed that a cement with higher viscosity than the marrow ensures stable development of the injection and a proper cement interdigitation inside the vertebra.

Zusammenfassung

The outcome of vertebroplasty is hard to predict due to its dependence on complex factors like bone cement and marrow rheologies. Cement leakage could occur if the procedure is done incorrectly, potentially causing adverse complications. A reliable simulation could predict the patient-specific outcome preoperatively and avoid the risk of cement leakage. Therefore, the aim of this work was to introduce a computationally feasible and experimentally validated model for simulating vertebroplasty. The developed model is a multiphase continuum-mechanical macro-scale model based on the Theory of Porous Media. The related governing equations were discretized using a combined finite element-finite volume approach by the so-called Box discretization. Three different rheological upscaling methods were used to compare and determine the most suitable approach for this application. For validation, a benchmark experiment was set up and simulated using the model. The influence of bone marrow and parameters like permeability, porosity, etc., was investigated to study the effect of varying conditions on vertebroplasty. The presented model could realistically simulate the injection of bone cement in porous materials when used with the correct rheological upscaling models, of which the semi-analytical averaging of the viscosity gave the best results. The marrow viscosity is identified as the crucial reference to categorize bone cements as 'high- 'or 'low-' viscosity in the context of vertebroplasty. It is confirmed that a cement with higher viscosity than the marrow ensures stable development of the injection and a proper cement interdigitation inside the vertebra.

Zusammenfassung

Goal: Skeletal muscle mechanics can be assessed in vivo using shear wave elastography. However, the impact of pennation angle on shear wave velocity (SWV) remains unclear. This study aims to quantify the effect by automatically aligning the ultrasound probe with muscle fiber orientation. Methods: We propose an automatic ultrasound probe alignment system and compare it to manual and no alignment. SWV of the gastrocnemius medialis muscle of ten volunteers was measured during rest and isometric contractions. Results: The SWV was different between the conditions (p = 0.008). The highest SWV was obtained during the automatic alignment and differences between the conditions were most pronounced during high-level contractions. The automatic system yielded more accurate alignment compared to a manual operator (p = 0.05). Conclusions: The present study indicates that pennation angle affects SWV, hence muscle fiber orientation must be considered to reliably interpret SWV. Using automatic alignment systems allows for more accurate alignment, improving the methodology of ultrasound elastography in skeletal muscles.

Zusammenfassung

Various studies have been recently conducted aiming at developing more sustainable cementitious systems so that concrete structures may not have a negative effect on the environment and are decomposed. It has been attempted to build sustainable binders by substituting silica fume, cement with fly ash, nano�silica, nano�alumina, and rice husk ash. In this paper, a series of experiments on concrete with different contents of rice husk ash (10\%, 15\%, and 20\%), nanoSiO2 (1\%, 2\%, 3\%, 4\%, 5\%, 6\%, 7\%, 8\%), and nanoAl2O3 (1\%, 2\%, 3\%, 4\%) are performed to analyze the durability and mechanical properties of samples under the curing condition of Caspian seawater. The workability, density, water penetration, chloride ion penetration, and compressive strength (at 7, 14, 28, and 90 day) of the samples were determined. The experimental results showed that workability decreased gradually with increasing additives content, while the compressive gradually increased. Among the additives, adding 8\% of the nanoSiO2 had the most significant effect on the improvement of compressive strength. Adding 8\% nanoSiO2 and 4\% nanoAl2O3 reduced the depth of water permeability by 53\% and 30\%, respectively. Furthermore, adding 8\% nanoSiO2 reduced chloride ion penetration by 85\%.

Zusammenfassung

MRI-based mathematical and computational modelling studies can contribute to a better understanding of the mechanisms governing cartilage's mechanical performance and cartilage disease. In addition, distinct modelling of cartilage is needed to optimize artificial cartilage production. These studies have opened up the prospect of further deepening our understanding of cartilage function. Furthermore, these studies reveal the initiation of an engineering-level approach to how cartilage disease affects material properties and cartilage function. Aimed at researchers in the field of MRI-based cartilage simulation, research articles pertinent to MRI-based cartilage modelling were identified, reviewed, and summarized systematically. Various MRI applications for cartilage modelling are highlighted, and the limitations of different constitutive models used are addressed. In addition, the clinical application of simulations and studied diseases are discussed. The paper's quality, based on the developed questionnaire, was assessed, and out of 79 reviewed papers, 34 papers were determined as high-quality. Due to the lack of the best constitutive models for various clinical conditions, researchers may consider the effect of constitutive material models on the cartilage disease simulation. In the future, research groups may incorporate various aspects of machine learning into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification, such as gait analysis.

Zusammenfassung

Finite element approximations of poroelastic materials are nowadays used within multiple applications. Due to wide variation of possible material parameters, robustness of the considered discretization is important. Within this contribution robust of discretization schemes, initially developed for Biot's theory, will be applied within the Theory of Porous Media. Selected numerical test-cases, special attention will be paid to incompressible and impermeable regimes, are conducted.

Zusammenfassung

Spasticity, following the neurological disorder of cerebral palsy (CP), describes a pathological condition, the central feature of which is involuntary and prolonged muscle contraction. The persistent resistance of spastic muscles to stretching is often followed by structural and mechanical changes in musculature. This leads to functional limitations at the respective joint. Focal injection of botulinum toxin type-A (BTX-A) is effectively used to manage spasticity and improve the quality of life of the patients. By blocking acetylcholine release at the neuromuscular junction and causing temporary muscle paralysis, BTX-A aims to reduce spasticity and hereby improve joint function. However, recent studies have indicated some contradictory effects such as increased muscle stiffness or a narrower range of active force production. The potential of these toxin- and atrophy-related alterations in worsening the condition of spastic muscles that are already subjected to changes should be further investigated and quantified. By focusing on the effects of BTX-A on muscle biomechanics and overall function in children with CP, this review deals with which of these goals have been achieved and to what extent, and what can await us in the future.

Zusammenfassung

We study fluid-saturated porous materials that undergo poro-elastic deformations in thin domains. The mechanics in such materials are described using a biphasic model based on the theory of porous media (TPM) and consisting of a system of differential equations for material’s displacement and fluid’s pressure. These equations are in general strongly coupled and nonlinear, such that exact solutions are hard to obtain and numerical solutions are computationally expensive. This paper reduces the complexity of the biphasic model in thin domains with a scale separation between domain’s width and length. Based on standard asymptotic analysis, we derive a reduced model that combines two sub-models. Firstly, a limit model consists of averaged equations that describe the fluid pore pressure and displacement in the longitudinal direction of the domain. Secondly, a corrector model re-captures the mechanics in the transverse direction. The validity of the reduced model is finally tested using a set of numerical examples. These demonstrate the computational efficiency of the reduced model, while maintaining reliable solutions in comparison with original biphasic TPM model in thin domain.

Zusammenfassung

The focus of this investigation lies on the development of a two-scale homogenization scheme for poro-elastic fluid-saturated porous media. For this purpose, the general concepts of the Theory of Porous Media (TPM) are combined with the FE2 method. After an introduction of the basics of TPM, the weak forms for the macroscopic and the microscopic scale will be formulated and the averaged macroscopic tangent moduli considering the microscale will be derived. Additionally, the formulation of lower level boundary conditions, which refer to the quantities that will be transmitted from the macro- to the microscale, in strict compliance with the Hill--Mandel homogeneity condition, is derived. Finally, a numerical example will be presented, pointing out the gained features of the methodology.

Zusammenfassung

A complete understanding of muscle mechanics allows for the creation of models that closely mimic human muscle function so they can be used to study human locomotion and evaluate surgical intervention. This includes knowledge of muscle-tendon parameters required for accurate prediction of muscle forces. However, few studies report experimental data obtained directly from whole human muscle due to the invasive nature of these experiments. This article presents an intraoperative, in vivo measurement protocol for whole muscle-tendon parameters that include muscle-tendon unit length, sarcomere length, passive tension, and active tension in response to external stimulation. The advantage of this protocol is the ability to obtain these rare experimental data in situ in addition to muscle volume and weight since the gracilis is also completely removed from the leg. The entire protocol including the surgical steps for gracilis harvest takes ~ 3 h. Actual testing of the gracilis where experimental data is measured takes place within a 30-min window during surgery.

Zusammenfassung

Abstract The present study applies two different machine learning (ML) algorithms to predict the stress-strain mapping for the non-linear behaviour of thermoplastic materials: a Long Short-Term Memory (LSTM) algorithm and a Feed-Forward Neural Network (FFNN). The approach of this work requires the generation of the stress-strain curve for specific material parameters. The training data are obtained from the von Mises material law and the Ramberg-Osgood equation. The four combinations of ML algorithms with constitutive laws are evaluated and show a good agreement with numerical data.

Zusammenfassung

Abstract The increasing number of cartilage diseases negatively affects the quality of life for a large part of the population. Understanding the mechanical properties of cartilage is a key component in investigating and mitigating the effects of such diseases. To describe the behavior of articular cartilage, a biphasic fiber-reinforced numerical model based on the Theory of Porous Media (TPM) has been developed. To possibly provide an alternative for the corresponding time-consuming computational simulations, the suitability of Artificial Neural Networks (ANNs) as surrogate models is investigated. For this purpose, the simulation results of a compression-relaxation test are compared with the predictions of the ANN.

Zusammenfassung

Abstract Quantum computing is a promising new computing paradigm that may yield both significant speedup over classical algorithms as well as new ways to think about problems and finding novel solution algorithms. While large-scale error-corrected quantum computers are still under development, a selection of noisy intermediate-scale quantum processing units is readily made available by some companies via cloud access. Despite the lack of error correction, these units can be used to test established quantum algorithms on custom problem setups. Here, we solve the finite element problem of a two-dimensional cantilever, completely fixed on one side and loaded on the opposite side, on a 15-qubit QPU from IBM.

Zusammenfassung

Quantum computing promises classically unparalleled benefits for various applications. Its properties are exploited in the Harrow-Hassidim-Lloyd (HHL) algorithm that, in conjunction with quantum phase estimation, is capable of constructing quantum states that are proportional to the solution of linear equation systems and does so exponentially faster than the fastest known classical algorithms. We explore this capability by computing the nodal displacements of a 1-dimensional loaded cantilever, discretized by using the finite element method (FEM).

Zusammenfassung

Musculoskeletal models rely heavily on the use of an anatomical dataset and clearly defined assumptions to accurately model the subject being studied. Therefore, it is important to understand the limitations of using musculoskeletal models to study individuals. This paper describes a method of measuring in vivo gracilis muscle-tendon unit length and presents a comparison of experimental data versus predictions from four musculoskeletal models in OpenSim. The largest errors occurred when the knee was fully extended. At this position, the absolute average muscle-tendon unit length error was 7% and the absolute average fiber length error was between 15% and 32%. However, the variability of these errors was significant. Manual linear scaling based on an anthropometric database did not capture the variability observed in subjects. The fiber length errors observed are predicted to have a significant impact on muscle force production that may not represent true subject specific force-length relationship of the gracilis.