Modelling the Heating Process in the Transient and Steady State of an In Situ Tape-Laying Machine Head

As the use of composite materials increases, the search for suitable automated processes gains relevance for guaranteeing production quality by ensuring the uniformity of the process, minimizing the amount of scrap generated, and reducing the time and energy consumption. Limitations on production by traditional means such as hand lay-up, vacuum bagging, and in-autoclave methods tend not to be as efficient when the size and shape complexity of the part being produced increases, motivating the search for alternative processes such as automated tape laying (ATL). This work aims to describe the process of modelling and simulating a composite ATL with in situ consolidation by characterizing the machine elements and using the finite differences method in conjunction with energy balances in order to create a digital twin of the process for further control design. The modelling approach implemented is able to follow the process dynamics when changes are made to the heating element and to predict the composite material temperature response, making it suitable for use as a digital twin of a production process using an ATL machine.

Image-Aided LiDAR Mapping Platform and Data Processing Strategy for Stockpile Volume Estimation

Stockpile quantity monitoring is vital for agencies and businesses to maintain inventory of bulk material such as salt, sand, aggregate, lime, and many other materials commonly used in agriculture, highways, and industrial applications. Traditional approaches for volumetric assessment of bulk material stockpiles, e.g., truckload counting, are inaccurate and prone to cumulative errors over long time. Modern aerial and terrestrial remote sensing platforms equipped with camera and/or light detection and ranging (LiDAR) units have been increasingly popular for conducting high-fidelity geometric measurements. Current use of these sensing technologies for stockpile volume estimation is impacted by environmental conditions such as lack of global navigation satellite system (GNSS) signals, poor lighting, and/or featureless surfaces. This study addresses these limitations through a new mapping platform denoted as Stockpile Monitoring and Reporting Technology (SMART), which is designed and integrated as a time-efficient, cost-effective stockpile monitoring solution. The novel mapping framework is realized through camera and LiDAR data-fusion that facilitates stockpile volume estimation in challenging environmental conditions. LiDAR point clouds are derived through a sequence of data collections from different scans. In order to handle the sparse nature of the collected data at a given scan, an automated image-aided LiDAR coarse registration technique is developed followed by a new segmentation approach to derive features, which are used for fine registration. The resulting 3D point cloud is subsequently used for accurate volume estimation. Field surveys were conducted on stockpiles of varying size and shape complexity. Independent assessment of stockpile volume using terrestrial laser scanners (TLS) shows that the developed framework had close to 1% relative error.

Coherence of global hydroclimate classification systems

Climate classification systems are useful for investigating future climate scenarios, water availability, and even socioeconomic indicators as they relate to climate dynamics. There are several classification systems that apply water and energy variables to create zone boundaries, although there has yet to be a simultaneous comparison of the structure and function of multiple existing climate classification schemes. Moreover, there are presently no classification frameworks that include evapotranspiration (ET) rates as a governing principle. Here, we developed a new system based on precipitation and potential evapotranspiration rates as well as three systems based on ET rates, which were all compared against four previously established climate classification systems. The within-zone similarity, or coherence, of several long-term hydroclimate variables was evaluated for each system based on the premise that the interpretation and application of a classification framework should correspond to the variables that are most coherent. Additionally, the shape complexity of zone boundaries was assessed for each system, assuming zone boundaries should be drawn efficiently such that shape simplicity and hydroclimate coherence are balanced for meaningful boundary implementation. The most frequently used climate classification system, Köppen–Geiger, generally had high hydroclimate coherence but also had high shape complexity. When compared to the Köppen–Geiger framework, the Water-Energy Clustering classification system introduced here showed overall improved or equivalent coherence for hydroclimate variables, yielded lower spatial complexity, and required only 2, compared to 24, parameters for its construction.

Modelling the Heating Process at Transient and Steady State of an In Situ Tape Laying Machine Head

As use of composite materials increases, the search for suitable automated processes gains relevance to guarantee production quality by ensuring uniformity of the process, minimizing the amount of generated scrap and reducing time and energy consumption. Limitations on production by traditional means such as hand lay-up, vacuum bagging and in-autoclave methods, tend not to be as efficient when the size and shape complexity of the part being produced increases, motivating the search for alternative processes such as the Automated Tape Laying (ATL). This work aims to describe the process of modelling and simulating a composite ATL with in situ consolidation by characterizing the machine elements, using the finite differences method in conjunction with energy balances, in order to create a digital twin of the process for further control design. The modelling approach implemented is able to follow the process dynamics when changes to the heating element are imposed as well as to predict the composite material temperature response, making it suitable to work as a digital twin of a production process using an ATL machine.

The annotation and analysis of complex 3D plant organs using 3DCoordX

A fundamental question in biology concerns how molecular and cellular processes become integrated during morphogenesis. In plants, characterization of 3D digital representations of organs at single-cell resolution represents a promising approach to addressing this problem. A major challenge is to provide organ-centric spatial context to cells of an organ. We developed several general rules for the annotation of cell position and embodied them in 3DCoordX, a user-interactive computer toolbox implemented in the open-source software MorphoGraphX. It enables rapid spatial annotation of cells even in highly curved biological shapes. With the help of 3DCoordX we obtained new insight by analyzing cellular growth patterns in organs of several species. For example, the data indicated the presence of a basal cell proliferation zone in the ovule primordium of Arabidopsis thaliana. Proof-of-concept analyses suggested a preferential increase in cell length associated with neck elongation in the archegonium of Marchantia polymorpha and variations in cell volume linked to central morphogenetic features of a trap of the carnivorous plant Utricularia gibba. Our work demonstrates the broad applicability of the developed strategies as they provide organ-centric spatial context to cellular features in plant organs of diverse shape complexity.

Differential Entropy: An Appropriate Analysis to Interpret the Shape Complexity of Self-Similar Organic Islands

Differential entropy, along with fractal dimension, is herein employed to describe and interpret the shape complexity of self-similar organic islands. The islands are imaged with in situ Atomic Force Microscopy, following, step-by-step, the evolution of their shape while deposition proceeds. The fractal dimension shows a linear correlation with the film thickness, whereas the differential entropy presents an exponential plateau. Plotting differential entropy versus fractal dimension, a linear correlation can be found. This analysis enables one to discern the 6T growth on different surfaces, i.e., native SiOx or 6T layer, and suggests a more comprehensive interpretation of the shape evolution. Changes in fractal dimension reflect rougher variations of the island contour, whereas changes in differential entropy correlates with finer contour details. The computation of differential entropy therefore helps to obtain more physical information on the island shape dependence on the substrate, beyond the standard description obtained with the fractal dimension.

Is Expansion or Regulation More Critical for Existing Protected Areas? A Case Study on China’s Eco-Redline Policy in Chongqing Capital

Protecting areas of important ecological value is one of the main approaches to safeguarding the Earth’s ecosystems. However, the long-term effectiveness of protected areas is often uncertain. Focusing on China’s ecological conservation redline policy (Eco-redline policy) introduced in recent years, this study attempted to examine the effectiveness of alternative policy interventions and their implications on future land-use and land-cover (LULC) patterns. A scenario analysis was employed to elucidate the implications of different policy interventions for Chongqing capital, one of the most representative cities in China. These interventions considered the spatial extent of Eco-redline areas (ERAs) and the management intensity within these areas. LULC data for two different periods from 2000 (first year) to 2010 (end year) were derived from satellite images and then used for future (2050) LULC projections, incorporating the various policy interventions. Furthermore, several landscape indices, including the shape complexity, contrast, and aggregation of forest patches were calculated for each scenario. After comparing the scenarios, our analysis suggests that the current extent of ERAs may not be sufficient, although their management intensity is. Therefore, we suggest that during the optimization of the Eco-redline policy, ERAs are gradually increased while maintaining their current management intensity.

A Comparison of Bottom-Up Models for Spatial Saliency Predictions in Autonomous Driving

Bottom-up saliency models identify the salient regions of an image based on features such as color, intensity and orientation. These models are typically used as predictors of human visual behavior and for computer vision tasks. In this paper, we conduct a systematic evaluation of the saliency maps computed with four selected bottom-up models on images of urban and highway traffic scenes. Saliency both over whole images and on object level is investigated and elaborated in terms of the energy and the entropy of the saliency maps. We identify significant differences with respect to the amount, size and shape-complexity of the salient areas computed by different models. Based on these findings, we analyze the likelihood that object instances fall within the salient areas of an image and investigate the agreement between the segments of traffic participants and the saliency maps of the different models. The overall and object-level analysis provides insights on the distinctive features of salient areas identified by different models, which can be used as selection criteria for prospective applications in autonomous driving such as object detection and tracking.

Shaping the Organ: A Biologist Guide to Quantitative Models of Plant Morphogenesis

Organ morphogenesis is the process of shape acquisition initiated with a small reservoir of undifferentiated cells. In plants, morphogenesis is a complex endeavor that comprises a large number of interacting elements, including mechanical stimuli, biochemical signaling, and genetic prerequisites. Because of the large body of data being produced by modern laboratories, solving this complexity requires the application of computational techniques and analyses. In the last two decades, computational models combined with wet-lab experiments have advanced our understanding of plant organ morphogenesis. Here, we provide a comprehensive review of the most important achievements in the field of computational plant morphodynamics. We present a brief history from the earliest attempts to describe plant forms using algorithmic pattern generation to the evolution of quantitative cell-based models fueled by increasing computational power. We then provide an overview of the most common types of “digital plant” paradigms, and demonstrate how models benefit from diverse techniques used to describe cell growth mechanics. Finally, we highlight the development of computational frameworks designed to resolve organ shape complexity through integration of mechanical, biochemical, and genetic cues into a quantitative standardized and user-friendly environment.

Implication of Buffer Zones Delineation Considering the Landscape Connectivity and Influencing Patch Structural Factors in Nature Reserves

Since habitat fragmentation results in species losses worldwide, considering the influence of buffer zones on the maintenance of connectivity provides a new perspective for buffer delimitation. In our study, the implications of buffer zones around nature reserves were studied at four sites in Fuzhou from the perspective of landscape connectivity based on a distance threshold of 1 km. We applied Graph-based connectivity indices at the landscape level and patch level to reveal the overall connectivity and patterns of change in patch importance for maintaining connectivity with various buffer zones. Based on the results of these analyses, we showed the relationship between structural factors and changes in patch importance by Spearman correlation analysis and redundancy analysis. The results indicate that in the sites with smaller habitat proportion (HP), the connectivity is relatively lower, and the changes in patch importance will be greater when the buffer zone increases. Different buffer zone sizes are suggested in four sites to maximize its benefits. Relatively small patches with high shape complexity and close proximity to patches outside the boundary contribute greatly to connectivity by acting as stepping stones.