Bryon C. Applequist, Zachary L. Motz, Anastasia Kyvelidou
<b>Background:</b> Linear methods of analysis of variability are concerned with the magnitude of variability and often consider deviations from a central mean as errors. The utilization of nonlinear tools to examine variability allows for the exploration and measurement of the patterns of variability displayed by the system. This methodology explores the deterministic properties of biological signals, in this case, gait, or how previous iterations within the gait cycle influence subsequent and future iterations. The nonlinear analysis of gait variability of the joint angle time series has not been investigated in developing children. <b>Methods</b>: We collected 3 min of treadmill walking data for 28 children between the ages of 2 and 10 years old and analyzed their joint angle time series using nonlinear methods of analysis (sample entropy, largest Lyapunov exponent, and recurrence quantification analysis). <b>Results</b>: Our results indicate that the nonlinear variability of children’s gait increases as children age. Interestingly, this contrasts with the findings from our previous work that showed a decrease in linear variability as children age. The combination of a decrease in linear variability, or a refined and improved stability of gait, as well as an increase in nonlinear variability, or an increase in the sophistication and quality of movement patterns, suggest an overall maturation of the neuromuscular system. <b>Conclusions</b>: Our study indicate that there is a refining of gait with age and motor maturation. This refining speaks to the overall multifaceted organization of systems that defines the maturation of gait.
Mechanics of engineering. Applied mechanics, Descriptive and experimental mechanics
Karanvir Singh Grewal, Roger E. Khayat, Kelly A. Ogden
The current study examines the influence of a varying gravity field and its interaction with density stratification. This represents a novel area in baroclinic flow analysis. The classical vortex and internal wave structures in stratified flows are shown to be significantly modified when gravity varies with height. Vortices may shift, stretch, or weaken depending on the direction and strength of gravity variation, and internal waves develop asymmetries or damping that are not present under constant gravity. We examine the influence of gravity variation on the flow of both homogeneous and density-stratified fluids in a channel with topography consisting of a Gaussian obstacle lying at the bottom of the channel. The flow is without inertia, induced by the translation of the top plate. Both the density and gravity are assumed to vary linearly with height, with the minimum density at the moving top plate. The narrow-gap approach is used to generate the flow field in terms of the pressure gradient along the top plate, which, in turn, is obtained in terms of the bottom topography and the three parameters of the problem, namely, the Froude number and the density and gravity gradients. The resulting stream function is a fifth-order polynomial in the vertical coordinate. In the absence of stratification, the flow is smooth, affected rather slightly by the variable topography, with an essentially linear drop in the pressure induced by the contraction. For a weak stratified fluid, the streamlines become distorted in the form of standing gravity waves. For a stronger stratification, separation occurs, and a pair of vortices generally appears on the two sides of the obstacle, the size of which depends strongly on the flow parameters. The influence of gravity stratification is closely coupled to that of density. We examine conditions where the coupling impacts the pressure and the velocity fields, particularly the onset of gravity waves and vortex flow. Only a mild density gradient is needed for flow separation to occur. The influence of the amplitude and width of the obstacle is also investigated.
Thermodynamics, Descriptive and experimental mechanics
This paper presents the design, implementation, and evaluation of a hybrid encryption framework that combines quantum key distribution, specifically a simulated BB84 protocol, with AES-256 encryption. The system enables secure file encryption by leveraging quantum principles for key generation and classical cryptography for data protection. It introduces integrity validation mechanisms, including HMAC verification and optional post-quantum digital signatures, ensuring robustness even in the presence of quantum-capable adversaries. The entire architecture is implemented in Python, with modular components simulating quantum key exchange, encryption, and secure packaging. Experimental results include visual testing of various attack scenarios, such as key tampering, HMAC failure, and file corruption, demonstrating the effectiveness and resilience of the approach. The proposed solution serves as a practical foundation for quantum-aware cybersecurity systems.
Jan Van den Berghe, Miguel A. Mendez, Yann Bartosiewicz
Ejectors are passive devices used in refrigeration, propulsion, and process industries to compress a secondary stream without moving parts. The engineering modeling of choking in these devices remains an open question, with two mechanisms-Fabri and compound choking-proposed in the literature. This work develops a unified one-dimensional framework that implements both mechanisms and compares them with axisymmetric Reynolds-Averaged Navier Stokes (RANS) data processed by cross-sectional averaging. The compound formulation incorporates wall and inter-stream friction and a local pressure-equalization procedure that enables stable integration through the sonic point, together with a normal shock reconstruction. The Fabri formulation is assessed by imposing the dividing streamline extracted from RANS, isolating the sonic condition while avoiding additional modeling assumptions. The calibrated compound model predicts on-design secondary mass flow typically within 2 % with respect to the RANS simulations, rising to 5 % for a strongly under-expanded primary jet due to the equal-pressure constraint. The Fabri analysis attains less than 1 % error in on-design entrainment but exhibits high sensitivity to the dividing streamline and closure, which limits predictive use beyond on-design. Overall, the results show that Fabri and compound mechanisms can coexist within the same device and operating map, each capturing distinct aspects of the physics and offering complementary modeling value. Nevertheless, compound choking emerges as the more general mechanism governing flow rate blockage, as evidenced by choked flows with a subsonic secondary stream.
Abstract There has been significant interest in researching droplet transport behavior on composite wetting surfaces. However, current research is primarily focused on modifying individual droplets and lacks an in‐depth investigation into high‐precision droplet storage. This study introduces a “billiard ball” droplet transport and storage platform (TSP) with differentiated areas. Within this platform, the volume of droplets stored in the area reaches a consistent threshold through droplet “scrambling,” inspired by the water‐gathering behavior of spiders. The TSP involves connecting two regions of different sizes using a three‐dimensional stepped wedge angle structure. However, this connection is not seamless, leaving a 2‐mm gap between the regions. This gap is intentionally designed to enable continuous droplet transfer while preventing any static migration. Through systematic experimental and simulation analysis, we investigated the influence of superhydrophilic pattern structures and parameters on quantitative droplet storage. We established a functional relationship between the pattern area and the stored volume, and analyzed the intrinsic mechanism of droplet collision separation. This enabled us to achieve on‐demand quantitative droplet storage and autonomize the storage process. The “billiard ball” droplet transport–storage platform proposed in this study holds promising applications in the fields of biomedical and organic chemistry.
Andrew Craig-Jones, Daniel R. Greene, Haley L. Gilbert
et al.
The purpose of this study was to compare average rate of oxygen consumption (VO<sub>2</sub>), slow component of oxygen consumption (VO<sub>2</sub> drift), heart rate (HR) and rating of perceived exertion (RPE) while wearing compression pants vs. a control garment during long-distance running. Methods: Nine injury-free and recreationally active participants (32 ± 11 years) were recruited for this study. Participants ran in full-leg compression pants (COMP) and a loose-fitting control garment (CON). Participants ran in each condition for 40 min at a preferred submaximal speed. The rate of oxygen consumption (VO<sub>2</sub>) was measured continuously via a metabolic cart throughout each condition. Both HR and RPE were recorded every 5 min during each condition. Oxygen consumption was averaged across the entirety of the steady state during the 40 min conditions for analysis. Additionally, the average from the first five minutes of the steady state was subtracted from the average of the last five minutes to assess VO<sub>2</sub>. A paired t-test was used to assess for differences for both variables. Both HR and RPE were each compared between conditions using 2 (garment) × 8 (time) repeated measure ANOVAs (α = 0.05). Results: There were no differences between VO<sub>2</sub> or VO<sub>2</sub> drift while running with full-leg compression pants vs. the control garment (<i>p</i> > 0.05). Neither RPE nor HR were influenced by the garments (<i>p</i> > 0.05) or time (<i>p</i> > 0.05) during each condition. Conclusion: Wearing compression pants did not result in reduced VO<sub>2</sub>, VO<sub>2</sub> drift, HR or RPE during a long-distance run. Although measured performance variables were not aided using compression pants, there were no negative effects to the use of compression pants.
Mechanics of engineering. Applied mechanics, Descriptive and experimental mechanics
Ulrich Römer, Stefan Hartmann, Jendrik-Alexander Tröger
et al.
In the framework of solid mechanics, the task of deriving material parameters from experimental data has recently re-emerged with the progress in full-field measurement capabilities and the renewed advances of machine learning. In this context, new methods such as the virtual fields method and physics-informed neural networks have been developed as alternatives to the already established least-squares and finite element-based approaches. Moreover, model discovery problems are starting to emerge and can also be addressed in a parameter estimation framework. These developments call for a new unified perspective, which is able to cover both traditional parameter estimation methods and novel approaches in which the state variables or the model structure itself are inferred as well. Adopting concepts discussed in the inverse problems community, we distinguish between all-at-once and reduced approaches. With this general framework, we are able to structure a large portion of the literature on parameter estimation in computational mechanics - and we can identify combinations that have not yet been addressed, two of which are proposed in this paper. We also discuss statistical approaches to quantify the uncertainty related to the estimated parameters, and we propose a novel two-step procedure for identification of complex material models based on both frequentist and Bayesian principles. Finally, we illustrate and compare several of the aforementioned methods with mechanical benchmarks based on synthetic and real data.
Abstract The self‐assembly of block copolymers (BCPs) within emulsion droplets is a flexible strategy for the preparation of polymer particles. This strategy permits the fine‐tuning of shapes, internal structures, and surface nanostructures of the polymer particles, thus allowing many applications. Although some literature has reviewed the BCP preparation via self‐assembly within a droplet, a comprehensive summary including in‐depth understanding, controllable preparation, and application is lacked. In this review, we systematically delve into the multiple mechanisms that drive BCP self‐assembly within emulsion droplets, such as commensurability effects for minimizing total free energy, interfacial instability, organized spontaneous emulsification, phase separation of multiple components, and entropy effects between BCPs and nanoparticles. Additionally, a strategy combining selective cross‐linking and disassembly can further generate Janus particles featuring unique structures. Next, various applications across multiple disciplines are discussed, including drug delivery, display, biomedical imaging, macromolecular separation, and fuel cells. Finally, we present an overview of the current challenges and future directions for BCP emulsion self‐assembly, covering mechanism investigation, molecular design, stability control, and application exploration. We anticipate deeper understanding, more varieties, enhanced performance, and broader applications can be achieved with BCP emulsion self‐assembly after addressing the challenge.
A methodology for defining variational principles for a class of PDE models from continuum mechanics is demonstrated, and some of its features explored. The scheme is applied to quasi-static and dynamic models of rate-independent and rate-dependent, single crystal plasticity at finite deformation.
Invariance theorems in analytical mechanics, such as Noether's theorem, can be adapted to continuum mechanics. For this purpose, it is useful to give a functional representation of the motion and to interpret the groups of invariance with respect to the space of reference associated with Lagrangian variables. A convenient method of calculus uses the Lie derivative. For instance, Kelvin theorems can be obtained by such a method.
The invariance theorems obtained in analytical mechanics and derived from Noether's theorems can be adapted to fluid mechanics. For this purpose, it is useful to give a functional representation of the fluid motion and to interpret the invariance group with respect to time in the quadri-dimensional reference space of Lagrangian variables. A powerful method of calculation uses Lie's derivative, and many invariance theorems and conservation laws can be obtained in fluid mechanics.
As the core powertrain component of electric vehicles, batteries release heat when charging and discharging due to the chemical reactions between the battery elements and internal resistance. To avoid problems resulting from abnormal temperatures, such as performance and lifespan issues, an effective battery cooling system is required. This paper presents a fundamental study of battery module liquid cooling through a three-dimensional numerical analysis. CFD numerical tests as conducted here are based on the heat transfer characteristics and on the liquid cooling theory, and the temperature distribution and thermal conductivity are analyzed qualitatively and quantitatively using Simcenter STAR CCM+ version 2016 (Siemens Digital Industries Software, Plano, TX, USA). A simulation uses a square-shell lithium-ion battery-made module with two different liquid cooling systems at different positions of the module. The results of the numerical study indicate that the bottom cooling system shows a better battery module temperature difference that is approximately 80% less than that of the side cooling system. For the side cooling system, it is better in terms of the maximum temperature of the battery module, which is approximately 20% lower than that in the bottom cooling system, but this system does not offer very good control of the temperature difference, which is also its greatest shortcoming compared to the bottom cooling system.
Thermodynamics, Descriptive and experimental mechanics
Isothermal turbulent flow around circular cylinders arranged side-by-side was numerically simulated on a commercial finite-volumes platform, ANSYS<sup>®</sup> CFX, version 2020 R2. The turbulence was modeled by using k-<i>ω</i> shear stress transport (k-ω SST). Three different Reynolds numbers were computed, <i>Re<sub>d</sub></i> = 200, 1000, and 3000, which were based on the cylinder diameter, d, the free stream velocity, <i>U</i><i>∞</i>, and the kinematic viscosity of the fluid, ν. Sided cylinders were spaced apart from each other, forming a <i>p/d</i> ratio equal to 2, which was kept constant throughout the computations regardless of changes in the Reynolds number. The drag coefficient, <i>C<sub>d</sub></i>, as well as its time traces, was evaluated along with the different wake topologies experienced by the cylinders (wide wake <i>WW</i> and narrow wake <i>NW</i>). The simulations were able to predict the bistable flow over the cylinders and the Cd changes associated with the wakes. Whenever a new wake topology was identified, the shape drag changed in accordance with the instantaneous pressure distribution. A laminar simulation was carried out for the lowest Reynolds number case, showing that the adopted turbulence model did not affect the dynamic response of the flow. The <i>Re<sub>d</sub></i> = 3000 case was compared to Afgan’s outcomes, whose simulations were carried out in a 3-D mesh using LES (Large Eddy Simulation), showing great agreement with their results.
Thermodynamics, Descriptive and experimental mechanics
This paper investigates the impact of combined axial through flow and radial mass flux on Taylor–Couette flow in a counter-rotating configuration, in which different branches of nontrivial solutions appear via Hopf bifurcations. Using direct numerical simulation, we elucidate flow structures, dynamics, and bifurcation behavior in qualitative and quantitative detail as a function of axial Reynolds numbers (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>R</mi><mi>e</mi></mrow></semantics></math></inline-formula>) and radial mass flux (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula>) spanning a parameter space with a very rich variety of solutions. We have determined nonlinear properties such as anharmonicity, asymmetry, flow rates (axial and radial) and torque for toroidally closed Taylor vortices and helical spiral vortices. Small to moderate radial flow <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula> initially decreases the symmetry of the different flows, before for larger values, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula>, the symmetry eventually increases, which appears to be congruent with the degree of anharmonicity. Enhancement in the total torque with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula> are elucidated whereby the strength varies for different flow structures, which allows for potential better selection and control. Further, depending on control parameters, heteroclinic connections (and cycles) of oscillatory type in between unstable and topological different flow structures are detected. The research results provide a theoretical basis for simple modification the conventional Taylor flow reactor with a combination of additional mass flux to enhance the mass transfer mechanism.
Thermodynamics, Descriptive and experimental mechanics
Luca Nanu, Carlos Perez Montenegro, Luigi Colangelo
et al.
In Networked Control Systems (NCS), the absence of physical communication links in the loop leads to relevant issues, such as measurement delays and asynchronous execution of the control commands. These issues may lead to unwanted control behaviours. This ArXiv paper is intended to give additional results to the work presented in "Embedded Model Control of Networked Control Systems: an Experimental Case-study". The last one presents an original approach, based on the Embedded Model Control, to deal with experimental scenarios characterized by asynchronous control timing. The effectiveness of the proposed approach is demonstrated with a differential-drive robot, first with high-fidelity simulations and finally with several experimental tests. Specifically, the present work aims to study the stability analysis of the EMC experimental setup and to give further experimental results, to complement those presented in the main paper, "Embedded Model Control of Networked Control Systems: an Experimental Case-study".
The bifurcation analysis of a film falling down an hybrid surface is conducted via the numerical solution of the governing lubrication equation. Instability phenomena, that lead to film breakage and growth of fingers, are induced by multiple contamination spots. Contact angles up to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>75</mn><mo>∘</mo></msup></semantics></math></inline-formula> are investigated due to the full implementation of the free surface curvature, which replaces the small slope approximation, accurate for film slope lower than <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mn>30</mn><mo>∘</mo></msup></semantics></math></inline-formula>. The dynamic contact angle is first verified with the Hoffman–Voinov–Tanner law in case of a stable film down an inclined plate with uniform surface wettability. Then, contamination spots, characterized by an increased value of the static contact angle, are considered in order to induce film instability and several parametric computations are run, with different film patterns observed. The effects of the flow characteristics and of the hybrid pattern geometry are investigated and the corresponding bifurcation diagram with the number of observed rivulets is built. The long term evolution of induced film instabilities shows a complex behavior: different flow regimes can be observed at the same flow characteristics under slightly different hybrid configurations. This suggest the possibility of controlling the rivulet/film transition via a proper design of the surfaces, thus opening the way for relevant practical application.
Thermodynamics, Descriptive and experimental mechanics
Florio M. Ciaglia, Fabio Di Cosmo, Alberto Ibort
et al.
Starting from the groupoid approach to Schwinger's picture of Quantum Mechanics, a proposal for the description of symmetries in this framework is advanced.It is shown that, given a groupoid $G\rightrightarrows Ω$ associated with a (quantum) system, there are two possible descriptions of its symmetries, one "microscopic", the other one "global".The microscopic point of view leads to the introduction of an additional layer over the grupoid $G$, giving rise to a suitable algebraic structure of 2-groupoid.On the other hand, taking advantage of the notion of group of bisections of a given groupoid, the global perspective allows to construct a group of symmetries out of a 2-groupoid.The latter notion allows to introduce an analog of the Wigner's theorem for quantum symmetries in the groupoid approach to Quantum Mechanics.
The rapid technological advances in the Internet of Things (IoT) allows the blueprint of Smart Cities to become feasible by integrating heterogeneous cloud/fog/edge computing paradigms to collaboratively provide variant smart services in our cities and communities. Thanks to attractive features like fine granularity and loose coupling, the microservices architecture has been proposed to provide scalable and extensible services in large scale distributed IoT systems. Recent studies have evaluated and analyzed the performance interference between microservices based on scenarios on the cloud computing environment. However, they are not holistic for IoT applications given the restriction of the edge device like computation consumption and network capacity. This paper investigates multiple microservice deployment policies on the edge computing platform. The microservices are developed as docker containers, and comprehensive experimental results demonstrate the performance and interference of microservices running on benchmark scenarios.
Pulsatile flow in the abdominal aorta and the renal arteries of three patients was studied numerically. Two of the patients had renal artery stenosis. The aim of the study was to assess the use of four types of indicators for determining the risk of new stenosis after revascularization of the affected arteries. The four indicators considered include the time averaged wall shear stress (<i>TAWSS</i>), the oscillatory shear index (<i>OSI</i>), the relative reference time (RRT) and a power law model based in platelet activation modeling but applied to the endothelium, named endothelium activation indicator (EAI). The results show that the indicators can detect the existing stenosis but are less successful in the revascularized cases. The <i>TAWSS</i> and, more clearly, the EAI approach seem to be better in predicting the risk for stenosis relapse at the original location and close to the post-stenotic dilatation. The shortcomings of the respective indicators are discussed along with potential improvements to endothelial activation modeling and its use as an indicator for risks of restenosis.
Thermodynamics, Descriptive and experimental mechanics