Generating Constructal Networks for Area-to-Point Conduction Problems Via Moving Morphable Components Approach

In this article, we focus on a generative design algorithm for area-to-point (AP) conduction problems in a Lagrangian framework. A physically meaningful continuous area to point path solution is generated through an adaptive growth procedure, which starts from the source point and extends spreading the whole conduction domain. This is achieved by using a set of special moving morphable components (MMCs) whose contour and skeleton are described explicitly by parameterized level-set surfaces. Unlike in the conventional methods where topology optimization was carried out in an Eulerian framework, the proposed optimizer is Lagrangian in nature, which is consistent with classical shape optimization approaches, giving great potential to reduce the total number of design variables significantly and also yielding more flexible modeling capability to control the structural feature sizes. By doing this, the growth elements are separated from the underlying finite element method (FEM) grids so that they can grow toward an arbitrary direction to form an optimized area-to-point path solution. The method is tested on an electromagnetic bandgap (EBG) power plane design example; both simulation and experiment verified the effectiveness of the proposed method.

Cunningham, Merce (1919 – 2009)

One of the twentieth century’s most influential dancers and choreographers, Merce Cunningham re-defined the genre of modern dance. He began his professional career as a member of the Martha Graham Company in 1939. However, by 1953, when he founded his own company, he had repudiated many of the prevailing beliefs and practices of previous modern dance pioneers. Prior to Cunningham, most modern dance choreographers (including Graham) vehemently rejected the fundamentals of classical ballet. Cunningham, by contrast, re-incorporated ballet’s emphasis on classical shape, line, elevation and intricate footwork. He offset these balletic elements with eccentric tilts and twists of the torso, back and arms. In the early 1950s, in collaboration with the composer John Cage, Cunningham also pioneered the use of ‘chance methodologies’ as a choreographic tool. Together, Cunningham and Cage fundamentally re-conceived the relationship between movement and music which had characterised virtually all earlier genres of choreography. In Cunningham’s dances, movement, sound and décor all remained independent of one another. Yet the underlying concept of collaboration remained fundamental to Cunningham’s dances, with celebrated composers and visual artists creating sound scores and designs for the company. Over the course of a career that spanned more than 60 years, Cunningham choreographed over 200 dances including Root of an Unfocus (1944), Sixteen Dances For Soloist and Company of Three (1951) Septet (1953), Suite for Five in Space and Time (1956), Summerspace (1958), Rune (1959), Winterbranch (1964), Variations V (1965) Walkaround Time (1968), Rainforest (1968), Sounddance (1975), Torse (1976), Quartet (1982), Fabrications (1987), CRWDSPCR (l993) and BIPED (1999).

Classification of mouse ultrasonic vocalizations using deep learning

Vocalizations are a widespread means of communication in the animal kingdom. Mice use a large repertoire of ultrasonic vocalizations (USVs) in different social contexts, for instance courtship, territorial dispute, dominance and mother-pup interaction. Previous studies have pointed to differences in the USVs in different context, sexes, strains and individuals, however, in many cases the outcomes of the analyses remained inconclusive.We here provide a more general approach to automatically classify USVs using deep neural networks (DNN). We classified the sex of the emitting mouse (C57Bl/6) based on the vocalization’s spectrogram, reaching unprecedented performance (~84% correct) in comparison with other techniques (Support Vector Machines: 64%, Ridge regression: 52%). Vocalization characteristics of individual mice only contribute mildly, and sex-only classification reaches ~78%. The performance can only partially be explained by a set of classical shape features, with duration, volume and bandwidth being the most useful predictors. Splitting estimation into two DNNs, from spectrograms to features (57-82%) and features to sex (67%) does not reach the single-step performance.In summary, the emitter’s sex can be successfully predicted from their spectrograms using DNNs, excelling over other classification techniques. In contrast to previous research, this suggests that male and female vocalizations differ in their spectrotemporal structure, recognizable even in single vocalizations.

Intermittent heat instabilities in an air plume

We report the results of heating experiments carried out in an abandoned limestone quarry close to Paris, in an isolated room of a volume of about 400 m3. A heat source made of a metallic resistor of power 100 W was installed on the floor of the room, at distance from the walls. High-quality temperature sensors, with a response time of 20 s, were fixed on a 2 m long bar. In a series of 24 h heating experiments the bar had been set up horizontally at different heights or vertically along the axis of the plume to record changes in temperature distribution with a sampling time varying from 20 to 120 s. When taken in averages over 24 h, the temperatures present the classical shape of steady-state plumes, as described by classical models. On the contrary, the temperature time series show a rich dynamic plume flow with intermittent trains of oscillations, spatially coherent, of large amplitude and a period around 400 s, separated by intervals of relative quiescence whose duration can reach several hours. To our knowledge, no specific theory is available to explain this behavior, which appears to be a chaotic interaction between a turbulent plume and a stratified environment. The observed behavior, with first-order factorization of a smooth spatial function with a global temporal intermittent function, could be a universal feature of some turbulent plumes in geophysical environments.

Intermittent heat instabilities in an air plume

We report the results of heating experiments carried in an abandoned limestone quarry close to Paris, in an isolated room of a volume of about 400 m3. A heat source made of a metallic resistor of power 100 W was installed on the floor of the room, at distance from the walls. High quality temperature sensors, with a response time of 20 s, were fixed on a 2-m long bar. In a series of 24-hour heating experiments the bar had been set up horizontally at different heights or vertically along the axis of the plume to record changes in temperature distribution with a sampling time varying from 20 s to 2 min. When taken in averages over 24 hours, the temperatures present the classical shape of steady state plumes, as described by classical models. On the contrary, the temperature time series show a rich dynamic plume flow with intermittent trains of oscillations, spatially coherent, of large amplitudes and a period around 400 s, separated by intervals of relative quiescence whose duration can reach several hours. To our knowledge, no specific theory is available to explain this behavior, which appears to be chaotic interaction between a turbulent plume and a stratified environment. The observed behavior, with first order factorization of a smooth spatial function with a global temporal intermittent function, could be a universal feature of some turbulent plumes in geophysical environments.

Lagrangian Description Based Topology Optimization—A Revival of Shape Optimization

Unlike in the previous treatment where shape and topology optimization were carried out essentially in an Eulerian framework, the aim of the present work is to show how to perform topology optimization based on a Lagrangian framework, which is seamlessly consistent with classical shape optimization approaches, with use of a set of moving morphable components (MMCs). It is hoped that the present work may light up the revival of classical shape optimization in structural design and optimization and inspire some subsequent works along this direction. Some representative examples are also provided to illustrate the effectiveness of the proposed solution framework.

Identifying plant species using architectural features in leaf microscopy images

This work proposes an analytical method to identify plant species based on microscopy images of the midrib cross-section of leaves. Unlike previous shape-based approaches based on the individual shape of external contours and cells, an architectural analysis is proposed, where the midrib is semi-automatically segmented and partitioned into histologically relevant structures composed of layers of cells and vascular structures. Using a sequence of morphological operations, a set of geometrical measures from the cells in each layer is extracted to produce a vector of features for species categorization. The method applied to a database containing 10 species of plants from the Brazilian flora achieved a success rate of 91.7%, outperforming other classical shape-based approaches published in the literature.