Scholarly Works, Mechanical Engineering

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Learning from Experience: A Faculty-Led Collaborative Inquiry Exploring Embedded Communication Skills Across Engineering Curricula
Biviano, Angelo; Branscome, Caroline; Burgoyne, Christine Bala; Carper, Kathleen; Iorio, Josh; Scarff, Kelly; Taylor, Ashley R.; Arena, Sara (ASEE Conferences, 2024-06-23)
This evidence-based practice paper describes a collaborative inquiry process to explore a critical question for engineering faculty: what are practical strategies for leveraging evidence-based practices to embed communication skills across core engineering curricula? Within engineering education, there is a growing consensus that communication skills are essential for engineering graduates. For example, the Accreditation Board for Engineering and Technology (ABET) distinctly highlights communication skills as a required student learning outcome for accreditation of engineering programs in ABET Criterion 3.3.: an ability to communicate effectively with a range of audiences. Numerous studies exploring engineers’ school-to-work transition suggest that communication is one of the most important skill sets for engineering practice according to both recent graduates (Passow, 2012) and industry (Male et. al, 2010). As the Engineer of 2020 Report concisely noted, “good engineering will require good communication” (National Academy of Engineering, 2004, p. 56). Despite the engineering education community’s shared vision for ensuring engineering graduates can communicate effectively, few practical examples exist to illuminate how faculty can leverage evidence-based practices to integrate communication skills into their existing technical curricula. Therefore, the purpose of this paper is to share seven practical case-based examples of strategies implemented in a spectrum of engineering disciplines and learning environments to support faculty in integrating communication skills into existing engineering curriculum. We first describe our collaborative inquiry process to create a “systematic structure for learning from experience” (Yorks & Kasl, 2002, p. 3). Our learning from experience is rooted in the reflections of faculty representing seven engineering departments who teach communication skills across a diverse range of engineering curricular contexts (e.g., course size, course level, technical subject, etc.) Next, we provide seven case studies of evidence-based strategies-in-action across this range of learning contexts, including both undergraduate and graduate education. For example, one case study discusses the integration of a community-focused debate project in a mining engineering undergraduate course to build students’ communications skills in rhetorical situation analysis while another study in a construction engineering management department attends to aspects of diversity and inclusion by promoting a writing process that begins with visual design. These case studies provide rich context for the learning environment and the implementation of the evidence-based practice, with the ultimate goal of supporting faculty in drawing connections to their own teaching strategies. Finally, we conclude by situating the case studies in the broader engineering education literature and sharing reflections for lessons learned on integration of communication instruction across existing engineering curricula.
Spinel oxide enables high-temperature self-lubrication in superalloys
Zhang, Zhengyu; Hershkovitz, Eitan; An, Qi; Liu, Liping; Wang, Xiaoqing; Deng, Zhifei; Baucom, Garrett; Wang, Wenbo; Zhao, Jing; Xin, Ziming; Moore, Lowell; Yi, Yao; Islam, Md Rezwan Ul; Chen, Xin; Cui, Bai; Li, Ling; Xin, Hongliang; Li, Lin; Kim, Honggyu; Cai, Wenjun (Nature Research, 2024-11-20)
The ability to lubricate and resist wear at temperatures above 600 °C in an oxidative environment remains a significant challenge for metals due to their high-temperature softening, oxidation, and rapid degradation of traditional solid lubricants. Herein, we demonstrate that high-temperature lubricity can be achieved with coefficients of friction (COF) as low as 0.10-0.32 at 600- 900 °C by tailoring surface oxidation in additively-manufactured Inconel superalloy. By integrating high-temperature tribological testing, advanced materials characterization, and computations, we show that the formation of spinel-based oxide layers on superalloy promotes sustained self-lubrication due to their lower shear strength and more negative formation and cohesive energy compared to other surface oxides. A reversible phase transformation between the cubic and tetragonal/monoclinic spinel was driven by stress and temperature during high temperature wear. To span Ni- and Cr-based ternary oxide compositional spaces for which little high-temperature COF data exist, we develop a computational design method to predict the lubricity of oxides, incorporating thermodynamics and density functional theory computations. Our finding demonstrates that spinel oxide can exhibit low COF values at temperatures much higher than conventional solid lubricants with 2D layered or Magnéli structures, suggesting a promising design strategy for selflubricating high-temperature alloys.
A model for a Langmuir sheath in a stagnating dense plasma with secondary ion formation
Martin, Christopher R.; Untaroiu, Alexandrina; Rahman, S. M. Mahbobur (IOP Publishing, 2024-04-24)
This simplified model provides solutions for the current-voltage characteristics of a sheath in a dense flowing plasma when surface chemistry contributes secondary ions. The problem is motivated by the recent discovery that strong transient signals in industrial ion current sensors are caused by chemical reactions with carbon in the steel being cut or welded by oxyfuel processes. The one-dimensional model considers a quasi-uniform dense plasma flowing towards and stagnating on an absorbing surface, above which there is a source of secondary ions. Because the secondary ions are formed directly in the plasma sheath, they have strong impacts on the current-voltage characteristic. With ionic Reynolds number, R, and integral length scale, α, secondary ion formation rate, Ω, and length scale, β, saturation currents are simply R + βΩ until β ≪ 1, at which point, new electrons cannot escape the sheath, and secondary ions have no effect. Floating potential, ϕ ∞, scales like exp ( ϕ ∞ ) ∝ R − 3 / 4 , and secondary ions have little impact unless β 2Ω > 1. Even then, floating potential is only weakly affected by secondary ion formation. The integral length scale, α, is not found to strongly affect the results.
Surrogate Model Development for Air Foil Thrust Bearings With Chevron-Patterned Trailing Edge
Yildiz, Saltuk; Untaroiu, Alexandrina (ASME, 2024-04-22)
Air foil thrust bearings provide some advantages over oil-lubricated thrust bearings. The use of these bearings reduces weight and increases dynamic stability, making it possible to reach high rotational speeds. However, as the bearing reaches high rotational speeds, the higher amount of heat generated results in reduced efficiency, deterioration, and even failure of the rotating machinery system. To overcome this, better thermal management is needed for air foil thrust bearings. Addressing this challenge, this study proposes the use of a chevron pattern at the trailing edge of the top foil to enhance air stream mixing, thus influencing heat dissipation. The main purpose of this study is to identify the optimal design parameters of the top foil trailing edge shape and provide a guideline for future air foil thrust bearing design. In this regard, 3D computational fluid dynamics (CFD) simulations are conducted to evaluate an air thrust foil bearing model performance. The highest temperature value occurring in the fluid and load-carrying capacity is selected as the output to find optimum design values. The design of experiments (DOE) technique is utilized for generating the sample points. A surrogate model is then used jointly with a multi-objective optimization to minimize the peak temperature in the air film and increase the load-carrying capacity. The optimal configuration is compared with the baseline, which is also used to validate the computational model with experimental data. This optimal design approach using a surrogate model can be used for further studies on improving the efficiency of air foil thrust bearings.
A Review of Biosensors and Their Applications
Katey, Bright; Voiculescu, Ioana; Penkova, Anita Nikolova; Untaroiu, Alexandrina (ASME, 2023-11-06)
This paper reviews sensors with nano- and microscale dimensions used for diverse biological applications. A biosensor converts biological responses into electrical signals. In recent years, there have been significant advancements in the design and development of biosensors that generated a large spectrum of biosensor applications including healthcare, disease diagnosis, drug delivery, environmental monitoring, and water and food quality monitoring. There has been significant work to enhance the performance of biosensors by improving sensitivity, reproducibility, and sensor response time. However, a key challenge of these technologies is their ability to efficiently capture and transform biological signals into electric, optic, gravimetric, electrochemical, or acoustic signals. This review summarizes the working principle of a variety of biosensors in terms of their classification, design considerations, and diverse applications. Other lines of research highlighted in this paper are focused on the miniaturization of biosensing devices with micro and nano-fabrication technologies, and the use of nanomaterials in biosensing. Recently wearable sensors have had important applications such as monitoring patients with chronic conditions in home and community settings. This review paper mentions applications of wearable technology. Machine learning is shown to help discover new knowledge in the field of medical applications. We also review artificial intelligence (AI) and machine learning (ML)-based applications.
Numerical Simulation of Impact of Different Redox Couples on Flow Characteristics and Electrochemical Performance of Deep Eutectic Solvent Electrolyte Flow Batteries
Xiao, Zhiyuan; Zhang, Ruiping; Lu, Mengyue; Ma, Qiang; Li, Zhuo; Su, Huaneng; Li, Huanhuan; Xu, Qian (MDPI, 2025-01-07)
A comprehensive, three-dimensional, macro-scale model was developed to simulate non-aqueous deep eutectic solvent (DES) electrolyte flow batteries. The model’s feasibility was validated by comparing the simulated polarization data with the experimental results. Utilizing this model, the work reported here compared the flow characteristics and electrochemical properties of electrolytes with different redox couples within the porous electrodes of the batteries. Despite variations in the active materials, the distribution of the electrolyte flow rate showed uniformity due to consistent electrode and flow channel designs, indicating that the structural design of electrodes and channels has a more significant impact on electrolyte flow than the physicochemical properties of the electrolytes themselves. This study also highlighted that TEMPO and Quinoxaline DES electrolytes exhibited less flow resistance and more uniform concentration distributions, which helped reduce overpotentials and enhance battery energy efficiency. Furthermore, this research identified that the highest average overpotentials occurred near the membrane for all the redox couples, demonstrating that electrochemical reactions in DES electrolyte flow batteries primarily occur in the region close to the membrane. This finding underscores the importance of optimizing active redox ions transport in electrolytes to enhance electrochemical reactions in the proximal membrane region, which is crucial for improving flow battery performance.
Forward/Backward Decomposition for Dispersive Wave Propagation Measurements
Corbin, Nicholas A.; Tarazaga, Pablo Alberto (MDPI, 2025-01-16)
Two complicating features commonly found in wave propagation applications include dispersion, i.e., frequency-dependent propagation velocity, and reflections, which introduce coherent noise. In this work, we present a signal processing technique which can be applied in a variety of applications to decompose signals into their forward- and backward-propagating components. The theory is presented, along with algorithmic implementation and experimental validation on a Timoshenko beam. The implications and potential utility of the method are briefly discussed.
Advancing Sustainability in Data Centers: Evaluation of Hybrid Air/Liquid Cooling Schemes for IT payload using Sea Water
Latif, Imran; Ashraf, Muhammad Mubashar; Haider, Umaima; Reeves, Gemma; Untaroiu, Alexandrina; Coelho, Fabio; Browne, Denis (IEEE, 2024-12)
The growth in cloud computing, big data, AI and -performance computing (HPC) necessitate the deployment of additional data centers (DC's) with high energy demands. The unprecedented increase in the Thermal Design Power (TDP) of the computing chips will require innovative cooling techniques. Furthermore, DC's are increasingly limited in their ability to add powerful GPU servers by power capacity constraints. As cooling energy use accounts for up to 40% of DC energy consumption, creative cooling solutions are urgently needed to allow deployment of additional servers, enhance sustainability and increase energy efficiency of DC's. The information in this study is provided from Start Campus' Sines facility supported by Alfa Laval for the heat exchanger and CO2 emission calculations.The study evaluates the performance and sustainability impact of various data center cooling strategies including an air-only deployment and a subsequent hybrid air/water cooling solution all utilizing sea water as the cooling source. We evaluate scenarios from 3MW to 15+1MW of IT load in 3MW increments which correspond to the size of heat exchangers used in the Start Campus' modular system design. This study also evaluates the CO2 emissions compared to a conventional chiller system for all the presented scenarios. Results indicate that the effective use of the sea water cooled system combined with liquid cooled systems improve the efficiency of the DC, plays a role in decreasing the CO2 emissions and supports in achieving sustainability goals.
Left-right tympanal size asymmetry in the parasitoid fly Ormia ochracea
Mikel-Stites, Max R.; Marek, Paul E.; Hellier, Madeleine E.; Staples, Anne E. (2024-08-02)
Ormia ochracea is a parasitoid fly notable for its impressive hearing abilities relative to its small size. Here, we use it as a model organism to investigate if minor size differences in paired sensory organs may be beneficial or neutral to an organism's perception abilities. We took high-resolution images of tympanal organs from 21 O. ochracea specimens and found a statistically significant surface area asymmetry (up to 6.88%) between the left and right membranes. Numerical experiments indicated that peak values of key sound localization variables increased with increasing tympanal asymmetry, which may explain features of the limited available physiological data.
A GNN-Based QSPR Model for Surfactant Properties
Ham, Seokgyun; Wang, Xin; Zhang, Hongwei; Lattimer, Brian; Qiao, Rui (MDPI, 2024-11-19)
Surfactants are among the most versatile molecules in the chemical industry because they can self-assemble in bulk solutions and at interfaces. Predicting the properties of surfactant solutions, such as their critical micelle concentration (CMC), limiting surface tension (γcmc), and maximal packing density (Γmax) at water–air interfaces, is essential to their rational design. However, the relationship between surfactant structure and these properties is complex and difficult to predict theoretically. Here, we develop a graph neural network (GNN)-based quantitative structure–property relationship (QSPR) model to predict the CMC, γcmc, and Γmax. Ninety-two surfactant data points, encompassing all types of surfactants—anionic, cationic, zwitterionic, and nonionic—are fed into the model, covering a temperature range of [20–30 °C], which contributes to its generalization across all surfactant types. We show that our models have high accuracy (R² = 0.87 on average in tests) in predicting the three parameters across all types of surfactants. The effectiveness of the QSPR model in capturing the variation of CMC, γcmc, and Γmax with molecular design parameters are carefully assessed. The curated dataset, developed model, and critical assessment of the developed model will contribute to the development of improved surfactants QSPR models and facilitate their rational design for diverse applications.
Chain-length-controllable upcycling of polyolefins to sulfate detergents
Munyaneza, Nuwayo Eric; Ji, Ruiyang; DiMarco, Adrian; Miscall, Joel; Stanley, Lisa; Rorrer, Nicholas; Qiao, Rui; Liu, Guoliang (Springer Nature, 2024-11-18)
Escalating global plastic pollution and the depletion of fossil-based resources underscore the urgent need for innovative end-of-life plastic management strategies in the context of a circular economy. Thermolysis is capable of upcycling end-of-life plastics to intermediate molecules suitable for downstream conversion to eventually high-value chemicals, but tuning the molar mass distribution of the products is challenging. Here we report a temperature-gradient thermolysis strategy for the conversion of polyethylene and polypropylene into hydrocarbons with tunable molar mass distributions. The whole thermolysis process is catalyst- and hydrogen-free. The thermolysis of polyethylene and polyethylene/polypropylene mixtures with tailored temperature gradients generated oil with an average chain length of ~C14. The oil featured a high concentration of synthetically useful α-olefins. Computational fluid dynamics simulations revealed that regulating the reactor wall temperature was the key to tuning the hydrocarbon distributions. Subsequent oxidation of the obtained α-olefins by sulfuric acid and neutralization by potassium hydroxide afforded sulfate detergents with excellent foaming behaviour and emulsifying capacity and low critical micelle concentration. Overall, this work provides a viable approach to producing value-added chemicals from end-of-life plastics, improving the circularity of the anthropogenic carbon cycle.
Gradient descent optimization of acoustic holograms for transcranial focused ultrasound
Sallam, Ahmed; Cengiz, Ceren; Pewekar, Mihir; Hoffmann, Eric; Legon, Wynn; Vlaisavljevich, Eli; Shahab, Shima (AIP Publishing, 2024-10-08)
Acoustic holographic lenses, also known as acoustic holograms, can change the phase of a transmitted wavefront in order to shape and construct complex ultrasound pressure fields, often for focusing the acoustic energy on a target region. These lenses have been proposed for transcranial focused ultrasound (tFUS) to create diffraction-limited focal zones that target specific brain regions while compensating for skull aberration. Holograms are currently designed using time-reversal approaches in full-wave time-domain numerical simulations. Such simulations need time-consuming computations, which severely limits the adoption of iterative optimization strategies. In the time-reversal method, the number and distribution of virtual sources can significantly influence the final sound field. Because of the computational constraints, predicting these effects and determining the optimal arrangement is challenging. This study introduces an efficient method for designing acoustic holograms using a volumetric holographic technique to generate focused fields inside the skull. The proposed method combines a modified mixed-domain method for ultrasonic propagation with a gradient descent iterative optimization algorithm. The findings are further validated in underwater experiments with a realistic 3D-printed skull phantom. This approach enables substantially faster holographic computation than previously reported techniques. The iterative process uses explicitly defined loss functions to bias the ultrasound field’s optimization parameters to specific desired characteristics, such as axial resolution, transversal resolution, coverage, and focal region uniformity, while eliminating the uncertainty associated with virtual sources in time-reversal techniques. The proposed techniques enable more rapid hologram computation and more flexibility in tailoring ultrasound fields for specific therapeutic requirements.
Reduced-Order Modeling for Dynamic System Identification with Lumped and Distributed Parameters via Receptance Coupling Using Frequency-Based Substructuring (FBS)
Hamedi, Behzad; Taheri, Saied (MDPI, 2024-10-19)
Paper presents an effective technique for developing reduced-order models to predict the dynamic responses of systems using the receptance coupling and frequency-based substructuring (RCFBS) method. The proposed approach is particularly suited for reconfigurable dynamic systems across various applications, like cars, robots, mechanical machineries, and aerospace structures. The methodology focuses on determining the overall system receptance matrix by coupling the receptance matrices (FRFs) of individual subsystems in a disassembled configuration. Two case studies, one with distributed parameters and the other with lumped parameters, are used to illustrate the application of this approach. The first case involves coupling three substructures with flexible components under fixed–fixed boundary conditions, while the second case examines the coupling of subsystems characterized by multiple masses, springs, and dampers, with various internal and connection degrees of freedom. The accuracy of the proposed method is validated against a numerical finite element analysis (FEA), direct methods, and a modal analysis. The results demonstrate the reliability of RCFBS in predicting dynamic responses for reconfigurable systems, offering an efficient framework for reduced-order modeling by focusing on critical points of interest without the need to account for detailed modeling with numerous degrees of freedom.
Exploring the role of diffusive coupling in spatiotemporal chaos
Raj, A.; Paul, Mark R. (AIP Publishing, 2024-10-07)
We explore the chaotic dynamics of a large one-dimensional lattice of coupled maps with diffusive coupling of varying strength using the covariant Lyapunov vectors (CLVs). Using a lattice of diffusively coupled quadratic maps, we quantify the growth of spatial structures in the chaotic dynamics as the strength of diffusion is increased. When the diffusion strength is increased from zero, we find that the leading Lyapunov exponent decreases rapidly from a positive value to zero to yield a small window of periodic dynamics which is then followed by chaotic dynamics. For values of the diffusion strength beyond the window of periodic dynamics, the leading Lyapunov exponent does not vary significantly with the strength of diffusion with the exception of a small variation for the largest diffusion strengths we explore. The Lyapunov spectrum and fractal dimension are described analytically as a function of the diffusion strength using the eigenvalues of the coupling operator. The spatial features of the CLVs are quantified and compared with the eigenvectors of the coupling operator. The chaotic dynamics are composed entirely of physical modes for all of the conditions we explore. The leading CLV is highly localized and localization decreases with increasing strength of the spatial coupling. The violation of the dominance of Oseledets splitting indicates that the entanglement of pairs of CLVs becomes more significant between neighboring CLVs as the strength of diffusion is increased.
Octopus-Inspired Adhesives with Switchable Attachment to Challenging Underwater Surfaces
Lee, Chanhong; Via, Austin C.; Heredia, Aldo; Adjei, Daniel A.; Bartlett, Michael D. (Wiley-VCH, 2024-10-09)
Adhesives that excel in wet or underwater environments are critical for applications ranging from healthcare and underwater robotics to infrastructure repair. However, achieving strong attachment and controlled release on difficult substrates, such as those that are curved, rough, or located in diverse fluid environments, remains a major challenge. Here, an octopus-inspired adhesive with strong attachment and rapid release in challenging underwater environments is presented. Inspired by the octopus’s infundibulum structure, a compliant, curved stalk, and an active deformable membrane for multi-surface adhesion are utilized. The stalk’s curved shape enhances conformal contact on large-scale curvatures and increases contact stress for adaptability to small-scale roughness. These synergistic mechanisms improve contact across multiple length scales, resulting in switching ratios of over 1000 within ≈30 ms with consistent attachment strength of over 60 kPa on diverse surfaces and conditions. These adhesives are demonstrated through the robust attachment and precise manipulation of rough underwater objects.
Covariant Lyapunov vectors of chaotic Rayleigh-Benard convection
Xu, M.; Paul, Mark R. (American Physical Society, 2016-06-10)
We explore numerically the high-dimensional spatiotemporal chaos of Rayleigh-Bénard convection using covariant Lyapunov vectors. We integrate the three-dimensional and time-dependent Boussinesq equations for a convection layer in a shallow square box geometry with an aspect ratio of 16 for very long times and for a range of Rayleigh numbers. We simultaneously integrate many copies of the tangent space equations in order to compute the covariant Lyapunov vectors. The dynamics explored has fractal dimensions of 20?Dλ?50, and we compute on the order of 150 covariant Lyapunov vectors. We use the covariant Lyapunov vectors to quantify the degree of hyperbolicity of the dynamics and the degree of Oseledets splitting and to explore the temporal and spatial dynamics of the Lyapunov vectors. Our results indicate that the chaotic dynamics of Rayleigh-Bénard convection is nonhyperbolic for all of the Rayleigh numbers we have explored. Our results yield that the entire spectrum of covariant Lyapunov vectors that we have computed are tangled as indicated by near tangencies with neighboring vectors. A closer look at the spatiotemporal features of the Lyapunov vectors suggests contributions from structures at two different length scales with differing amounts of localization.
Stochastic dynamics of micron-scale doubly clamped beams in a viscous fluid
Villa, M. M.; Paul, Mark R. (American Physical Society, 2009-05-28)
We study the stochastic dynamics of doubly clamped micron-scale beams in a viscous fluid driven by Brownian motion. We use a thermodynamic approach to compute the equilibrium fluctuations in beam displacement that requires only deterministic calculations. From calculations of the autocorrelations and noise spectra we quantify the beam dynamics by the quality factor and resonant frequency of the fundamental flexural mode over a wide range of experimentally accessible geometries. We consider beams with uniform rectangular cross section and explore the increased quality factor and resonant frequency as a baseline geometry is varied by increasing the width, increasing the thickness, and decreasing the length. The quality factor is nearly doubled by tripling either the width or the height of the beam. Much larger improvements are found by decreasing the beam length, however this is limited by the appearance of additional modes of fluid dissipation. Overall, the stochastic dynamics of the wider and thicker beams are well predicted by a two-dimensional approximate theory beyond what may be expected based upon the underlying assumptions, whereas the shorter beams require a more detailed analysis.
Quantifying spatiotemporal chaos in Rayleigh-Benard convection
Karimi, A.; Paul, Mark R. (American Physical Society, 2012-04-02)
Using large-scale parallel numerical simulations we explore spatiotemporal chaos in Rayleigh-Bénard convection in a cylindrical domain with experimentally relevant boundary conditions. We use the variation of the spectrum of Lyapunov exponents and the leading-order Lyapunov vector with system parameters to quantify states of high-dimensional chaos in fluid convection. We explore the relationship between the time dynamics of the spectrum of Lyapunov exponents and the pattern dynamics. For chaotic dynamics we find that all of the Lyapunov exponents are positively correlated with the leading-order Lyapunov exponent, and we quantify the details of their response to the dynamics of defects. The leading-order Lyapunov vector is used to identify topological features of the fluid patterns that contribute significantly to the chaotic dynamics. Our results show a transition from boundary-dominated dynamics to bulk-dominated dynamics as the system size is increased. The spectrum of Lyapunov exponents is used to compute the variation of the fractal dimension with system parameters to quantify how the underlying high-dimensional strange attractor accommodates a range of different chaotic dynamics.
Chaotic Rayleigh-Benard convection with finite sidewalls
Xu, M.; Paul, Mark R. (American Physical Society, 2018-07-02)
We explore the role of finite sidewalls on chaotic Rayleigh-Bénard convection. We use large-scale parallel spectral-element numerical simulations for the precise conditions of experiment for cylindrical convection domains. We solve the Boussinesq equations for thermal convection and the conjugate heat transfer problem for the energy transfer at the solid sidewalls of the cylindrical domain. The solid sidewall of the convection domain has finite values of thickness, thermal conductivity, and thermal diffusivity. We compute the Lyapunov vectors and exponents for the entire fluid-solid coupled problem. We quantify the chaotic dynamics of convection over a range of thermal sidewall boundary conditions. We find that the dynamics become less chaotic as the thermal conductivity of the sidewalls increases as measured by the value of the fractal dimension of the dynamics. The thermal conductivity of the sidewall is a stabilizing influence; the heat transfer between the fluid and solid regions is always in the direction to reduce the fluid motion near the sidewalls. Although the heat interaction for strongly conducting sidewalls is only about 1% of the heat transfer through the fluid layer, it is sufficient to reduce the fractal dimension of the dynamics by approximately 25% in our computations.
Length scale of a chaotic element in Rayleigh-Benard convection
Karimi, A.; Paul, Mark R. (American Physical Society, 2012-12-20)
We describe an approach to quantify the length scale of a chaotic element of a Rayleigh-Bénard convection layer exhibiting spatiotemporal chaos. The length scale of a chaotic element is determined by simultaneously evolving the dynamics of two convection layers with a unidirectional coupling that involves only the time-varying values of the fluid velocity and temperature on the lateral boundaries of the domain. In our results we numerically simulate the full Boussinesq equations for the precise conditions of experiment. By varying the size of the boundary used for the coupling we identify a length scale that describes the size of a chaotic element. The length scale of the chaotic element is of the same order of magnitude, and exhibits similar trends, as the natural chaotic length scale that is based upon the fractal dimension.

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