Dynamic mode decomposition (DMD) is a factorization and dimensionality reduction technique for data sequences. In its most common form, it processes high-dimensional sequential measurements, extracts coherent structures, isolates dynamic behavior, and reduces complex evolution processes to their dominant features and essential components. The decomposition is intimately related to Koopman analysis and, since its introduction, has spawned various extensions, generalizations, and improvements. It has been applied to numerical and experimental data sequences taken from simple to complex fluid systems and has also had an impact beyond fluid dynamics in, for example, video surveillance, epidemiology, neurobiology, and financial engineering. This review focuses on the practical aspects of DMD and its variants, as well as on its usage and characteristics as a quantitative tool for the analysis of complex fluid processes. Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 54 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Natalia A. Guk, Yurii M. Matsevity, Volodymyr O. Povhorodnii
et al.
The paper proposes a method for determining maximum thermoload from the temperature stress measured with a value by solving the inverse problem of thermoelasticity for canonical bodies. Determination of maximum thermoload is of significant practical importance when conducting non-destructive testing. It is important to regulate temperature and force loads, when thermostresses in structural elements will be achieved within permissible limits. For example, the tensile strength of the D16T material is exceeded at a heat flux of 6400 W/m2. This indicates the high heat resistance of the material D16T. To find values, the method of solving inverse problems of thermoelasticity was used. To obtain a stable and accurate solution to the inverse problem of thermoelasticity and thermoconductivity, the numerical finite element method and the Tikhonov method with the search for the regularization parameter are used. The Tikhonov method uses a stabilizing functional with a regularization parameter. The search of the regularizator is carried out using an algorithm for calculating the root of a nonlinear equation, which allows increasing the accuracy of results. The Tikhonov method has an error within 5%. The cost-effectiveness of the method lies in replacing complex and expensive experimental studies of objects with numerical experiments. The proposed methodology allows determining the loads at which it will be destroyed without bringing the object to destruction. Solving internal inverse problems of thermoelasticity is a complex and actual issue, especially in connection with the development of computers. This method applies to energy and aviation engineering facilities under high temperature and force loads.
Shinde Bharti M., Sayyad Atteshamuddin S., Naik Nitin S.
Static response of simply supported functionally graded (FG) shallow shells using a new higher-order shear and normal deformation theory is focused in this article. The effects of transverse strains and stresses on the bending response of FG shell are considered by the present theory. The current theory considers the impacts of transverse normal and shear deformations that meet the requirements for traction-free boundary conditions. The virtual work principle is applied to the mathematical formulation of the present theory. The simply supported doubly curved shallow shell problems under the static transverse load are analyzed using Navier’s solution technique. To verify the existing theory, the current results are, whenever possible, compared with those that have already been published. Additionally, a few benchmark results are presented in this article that will be helpful to researchers in the future.
Abstract Photoacoustic dual-comb spectroscopy (DCS), converting spectral information in the optical frequency domain to the audio frequency domain via multi-heterodyne beating, enables background-free spectral measurements with high resolution and broad bandwidth. However, the detection sensitivity remains limited due to the low power of individual comb lines and the lack of broadband acoustic resonators. Here, we develop cavity-enhanced photoacoustic DCS, which overcomes these limitations by using a high-finesse optical cavity for the power amplification of dual-frequency combs and a broadband acoustic resonator with a flat-top frequency response. We demonstrate high-resolution spectroscopic measurements of trace amounts of C2H2, NH3 and CO in the entire telecommunications C-band. The method shows a minimum detection limit of 0.6 ppb C2H2 at the measurement time of 100 s, corresponding to the noise equivalent absorption coefficient of 7 × 10−10 cm−1. The proposed cavity-enhanced photoacoustic DCS may open new avenues for ultrasensitive, high-resolution, and multi-species gas detection with widespread applications.
Rudrajit Choudhuri, Ambareesh Ramakrishnan, Amreeta Chatterjee
et al.
Generative AI (genAI) tools (e.g., ChatGPT, Copilot) have become ubiquitous in software engineering (SE). As SE educators, it behooves us to understand the consequences of genAI usage among SE students and to create a holistic view of where these tools can be successfully used. Through 16 reflective interviews with SE students, we explored their academic experiences of using genAI tools to complement SE learning and implementations. We uncover the contexts where these tools are helpful and where they pose challenges, along with examining why these challenges arise and how they impact students. We validated our findings through member checking and triangulation with instructors. Our findings provide practical considerations of where and why genAI should (not) be used in the context of supporting SE students.
Mario Mally, Bernard Kapidani, Melina Merkel
et al.
The simulation of electromagnetic devices with complex geometries and large-scale discrete systems benefits from advanced computational methods like IsoGeometric Analysis and Domain Decomposition. In this paper, we employ both concepts in an Isogeometric Tearing and Interconnecting method to enable the use of parallel computations for magnetostatic problems. We address the underlying non-uniqueness by using a graph-theoretic approach, the tree-cotree decomposition. The classical tree-cotree gauging is adapted to be feasible for parallelization, which requires that all local subsystems are uniquely solvable. Our contribution consists of an explicit algorithm for constructing compatible trees and combining it with a dual-primal approach to enable parallelization. The correctness of the proposed approach is proved and verified by numerical experiments, showing its accuracy, scalability and optimal convergence.
Zhihui Wen, Julio Andrés Iglesias Martínez, Yabin Jin
et al.
Localized topological modes with high robustness to various perturbations are receiving increasing attention. Recently, zero-order topological vortex modes have been designed in phononic structures, in analogy with zero-energy fermionic states modulated by Jackiw-Rossi binding mechanism. Such localized modes may have potential applications for biosensing, bioimaging and on-chip communication. In this work, we propose a pillared phononic plate with a Kekulé distortion of pillars position to bind topological modes at a vortex core via dispersion engineering. The phase winding and amplitude diagrams of the topological vortex mode are observed experimentally. It is found that existence of vibration peaks and corresponding mode patterns are strongly robust against the random perturbation of resonant frequencies of pillars at the vortex core. We further design a topological resonant sensor for mass sensitivity. The frequency of the topological vortex mode is almost linearly sensitive to added small mass at the vortex core in terms of mass values and positions. The proposed pillared plates provide a platform for potential applications such as energy localization and harvesting, remote health monitoring.
Materials of engineering and construction. Mechanics of materials
Aranyak Chakravarty, Aranyak Chakravarty, Mahesh V. Panchagnula
et al.
Respiratory viruses, such as SARS-CoV-2, preliminarily infect the nasopharyngeal mucosa. The mechanism of infection spread from the nasopharynx to the deep lung–which may cause a severe infection—is, however, still unclear. We propose a clinically plausible mechanism of infection spread to the deep lung through droplets, present in the nasopharynx, inhaled and transported into the lower respiratory tract. A coupled mathematical model of droplet, virus transport and virus infection kinetics is exercised to demonstrate clinically observed times to deep lung infection. The model predicts, in agreement with clinical observations, that severe infection can develop in the deep lung within 2.5–7 days of initial symptom onset. Results indicate that while fluid dynamics plays an important role in transporting the droplets, infection kinetics and immune responses determine infection growth and resolution. Immune responses, particularly antibodies and T-lymphocytes, are observed to be critically important for preventing infection severity. This reinforces the role of vaccination in preventing severe infection. Managing aerosolization of infected nasopharyngeal mucosa is additionally suggested as a strategy for minimizing infection spread and severity.
Agriculture has a good stake in the world’s GDP. In many countries, agriculture and allied sectors have a good stake in national GDP. This paper covers details related to livestock since 1960s. The workforce has managed livestock for many decades. The workforce increases as the number of animals increases; it is an energy, time-consuming, and economically costly approach. Apart from it, there is no assurance about animal welfare in case of diseases, breeding, and feed intake issues. In the 21st century of digitalization, technology has a key role in improving overall monitoring, controlling, and processing in livestock management. This paper has gone thoroughly into the manual and automated livestock farm management, aiming welfare of animals, livestock products, consumers’ benefit, and sustainable environmental approaches.
We simulate the head-on collision between vortex rings with circulation Reynolds numbers of 4000 using an adaptive, multiresolution solver based on the lattice Green's function. The simulation fidelity is established with integral metrics representing symmetries and discretization errors. Using the velocity gradient tensor and structural features of local streamlines, we characterize the evolution of the flow with a particular focus on its transition and turbulent decay. Transition is excited by the development of the elliptic instability, which grows during the mutual interaction of the rings as they expand radially at the collision plane. The development of antiparallel secondary vortex filaments along the circumference mediates the proliferation of small-scale turbulence. During turbulent decay, the partitioning of the velocity gradients approaches an equilibrium that is dominated by shearing and agrees well with previous results for forced isotropic turbulence. We also introduce new phase spaces for the velocity gradients that reflect the interplay between shearing and rigid rotation and highlight geometric features of local streamlines. In conjunction with our other analyses, these phase spaces suggest that, while the elliptic instability is the predominant mechanism driving the initial transition, its interplay with other mechanisms, e.g. the Crow instability, becomes more important during turbulent decay. Our analysis also suggests that the geometry-based phase space may be promising for identifying the effects of the elliptic instability and other mechanisms using the structure of local streamlines. Moving forward, characterizing the organization of these mechanisms within vortices and universal features of velocity gradients may aid in modelling turbulent flows.
Heisenberg's breakthrough in his July 1925 paper that set in motion the development of Quantum Mechanics through subsequent papers by Born, Jordan, Heisenberg and also Dirac (from 1925 to 1927) is reexamined through a modern lens. In this paper, we shall discuss some new perspectives on (i) what could be the guiding intuitions for his discoveries and (ii) the origin of the Born-Jordan-Heisenberg canonical quantization rule. From this vantage point we may get an insight into Einstein's Quantum Riddle (Lande1974,Sommerfeld1918,Born1926) and a possible glimpse of what might come next after the last 100 years of Heisenberg's quantum mechanics.