scholarly journals Optimizing Stand Spatial Structure by Using Neighborhood-Based Quantitative Indicators: A Case of Boreal Forests

2021 ◽  
Author(s):  
Lingbo Dong ◽  
Pete Bettinger ◽  
Zhaogang Liu
Keyword(s):  
Boreal Forests ◽  
Simulated Annealing Algorithm ◽  
Secondary Forest ◽  
Structural Characteristics ◽  
Structural Parameters ◽  
Tree Level ◽  
Partial Cutting ◽  
Broad Leaved Forest ◽  
Objective Function Values ◽  
Operational Constraints

Abstract Background: Over the past fifty years, societies have placed increasing demands on forests, and their use has shifted gradually from wood production to the diversified benefits and functions of ecosystem services. The effects of neighborhood-based structural characteristics on regulating growth and promoting sustainability have therefore drawn much attention. However, direction for managing natural mixed forests using neighborhood-based indicators are still not clear.Methods: In this study, a tree-level harvest planning tool that considers four neighborhood-based structural parameters (species mingling, diametric differentiation, horizontal spatial pattern and crowdedness of trees) while concurrently recognizing other operational constraints, was developed using simulated annealing algorithm. The approach was applied to four 1-ha mapped stands in northeast China, namely a natural larch forest (NLF), a natural birch forest (NBF), a natural secondary forest (SEF), and a Korean pine broad-leaved forest (KBF). Results: The tree-level harvest optimization improved the objective function values by approximately 78.33% of NLF, and 134.96% of NBF, and 156.70% of SEF and 252.95%, respectively. The optimal harvest intensities for partial cutting activities varied from 22.16% (SEF) to 26.07% (NBF) of the standing volume. In evaluating the four neighborhood-based structural parameters, both species mingling and crowdedness have the highest priority to be used in structure-based forest management.Conclusions: Our results demonstrated that that the commonly used neighborhood-based structural parameters could be used to control the spatial layout of potential harvest trees, in turn may be conducive to regulate the growth and stability of forests.

scholarly journals Coupled Fluid–Solid Numerical Simulation for Flow Field Characteristics and Supporting Performance of Flexible Support Cylindrical Gas Film Seal

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 97
Author(s):  
Junfeng Sun ◽  
Meihong Liu ◽  
Zhen Xu ◽  
Taohong Liao ◽  
Xiangping Hu ◽  
...  
Keyword(s):  
Flow Field ◽  
Film Thickness ◽  
Fluid Dynamic ◽  
Structural Characteristics ◽  
Structural Parameters ◽  
Equivalent Stress ◽  
Three Dimensional ◽  
High Rotational Speed ◽  
Flexible Support ◽  
Flow Field Characteristics

A new type of cylindrical gas film seal (CGFS) with a flexible support is proposed according to the working characteristics of the fluid dynamic seal in high-rotational-speed fluid machinery, such as aero-engines and centrifuges. Compared with the CGFS without a flexible support, the CGFS with flexible support presents stronger radial floating characteristics since it absorbs vibration and reduces thermal deformation of the rotor system. Combined with the structural characteristics of a film seal, an analytical model of CGFS with a flexible wave foil is established. Based on the fluid-structure coupling analysis method, the three-dimensional flow field of a straight-groove CGFS model is simulated to study the effects of operating and structural parameters on the steady-state characteristics and the effects of gas film thickness, eccentricity, and the number of wave foils on the equivalent stress of the flexible support. Simulation results show that the film stiffness increases significantly when the depth of groove increases. When the gas film thickness increases, the average equivalent stress of the flexible support first decreases and then stabilizes. Furthermore, the number of wave foils affects the average foils thickness. Therefore, when selecting the number of wave foils, the support stiffness and buffer capacity should be considered simultaneously.

Synthetic Transfer Zone Characterization Using Seismic Attributes: An Example from the Parihaka Fault System in the Taranaki Basin, New Zealand.

2021 ◽  
pp. 1-73
Author(s):  
Pierre Karam ◽  
Shankar Mitra ◽  
Kurt Marfurt ◽  
Brett M. Carpenter
Keyword(s):  
New Zealand ◽  
Structural Characteristics ◽  
Structural Parameters ◽  
Seismic Attributes ◽  
Fault System ◽  
Structural Interpretation ◽  
Transfer Zones ◽  
Seismic Characterization ◽  
The Individual ◽  
Transfer Zone

Synthetic transfer zones develop between fault segments which dip in the same direction, with relay ramps connecting the fault blocks separated by the different fault segments. The characteristics of the transfer zones are controlled by the lithology, deformation conditions, and strain magnitude. The Parihaka fault is a NE-SW trending set of three major en-echelon faults connected by relay ramps in the Taranaki Basin, New Zealand. The structure in the basin is defined by extension during two episodes of deformation between the late Cretaceous and Paleocene and between the Late Miocene and recent. To better understand the evolution of a synthetic transfer zone, we study the geometry and secondary faulting between the individual fault segments in the Parihaka fault system using structural interpretation of 3D seismic data and seismic attributes. This interpretation allows for a unique application of seismic attributes to better study transfer zones. Seismic attributes, including coherence, dip, and curvature are effective tools to understand the detailed geometry and variation in displacement on the individual faults, the nature of secondary faulting along the transfer zones, and the relationship between the faults and drape folds. Seismic characterization of the fault system of Miocene to Pliocene age horizons highlights variations in the degree of faulting, deformation, and growth mechanism associated with different stages of transfer zone development. Coherence, dip, and curvature attributes show a direct correlation with structural parameters such as deformation, folding, and breaching of relay ramps.. All three attributes enhance the visualization of the major and associated secondary faults and better constrain their tectonic history. The observed correlation between seismic attributes and structural characteristics of transfer zones can significantly improve structural interpretation and exploration workflow.

Optimization of Semimagnetic Semiconductor-Based Nanostructures for Spintronic Applications

2006 ◽  
Vol 518 ◽  
pp. 35-40
Author(s):  
J. Radovanović ◽  
V. Milanović ◽  
Z. Ikonić ◽  
D. Indjin
Keyword(s):  
Magnetic Field ◽  
External Magnetic Field ◽  
Simulated Annealing Algorithm ◽  
Structural Parameters ◽  
Zeeman Effect ◽  
Parameters Optimization ◽  
Potential Barriers ◽  
Annealing Algorithm ◽  
Electrical Bias ◽  
Spin Filtering

We have analyzed the spin-filtering effects of the electron current in asymmetric ZnSe/Zn1-xMnxSe multilayer structures, under the influence of both an external magnetic field and a bias voltage. In this type of semiconductor systems, conduction band electrons interact with 3d electrons of the magnetic Mn2+ ions. Because of this sp-d exchange interaction, an external magnetic field modulates the effective potential profile seen by spin-up and spin-down electrons, giving rise to a large Zeeman effect. It is found that the degree of spin polarization changes significantly when the electrical bias is switched from forward to reverse, thus the proposed structure displays obvious behavior of spin-filter diode. This originates from the effective “lifting” of the potential for spin-up electrons, which tunnel through actual potential barriers. Structural parameters optimization, with the goal of maximizing the spin-filtering coefficient, was performed by using simulated annealing algorithm. The described effect may be important for designing new tunable spin-based multifunctional semiconductor devices.

Abstract TP436: Dysfunctional Cerebral Neovascularization And Remodeling Patterns In Obese And Lean Models Of Type 2 Diabetes

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Roshini Prakash ◽  
Maribeth Johnson ◽  
Susan C Fagan ◽  
Adviye Ergul
Keyword(s):  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Structural Characteristics ◽  
Structural Parameters ◽  
Volume Density ◽  
3 Dimensional ◽  
Gk Rats ◽  
Dimensional Reconstruction ◽  
Branch Density

We previously reported intense pial cerebral collateralization and arteriogenesis in a mild and lean model of type 2 diabetes, Goto-Kakizaki (GK) rats. Further 3-dimensional fluroscein (FITC) imaging studies revealed regional differences in increased cerebral neovascularization which was associated with poor vessel wall maturity. Building upon these findings, the goals of this study were a) to compare and contrast this pathological neovascularization pattern in db/db mice and GK models of diabetes, and b) determine the effect of glycemic control on erratic cerebral neovascularization. Total vascular volume, density and surface area as well as structural parameters including microvessel/macrovessel ratio, non-FITC perfusing vessel abundance, penetrating arteriole (PA) branching density and diameter, and tortuosity were measured by 3 dimensional reconstruction of FITC stained vasculature using Z-stacked images obtained with confocal microscopy. Lean GK rats exhibited an increase in both micro and macrovessel density, non-perfusing vessel abundance, branch density, diameter and tortuosity. Glycemic control with metformin prevented these changes. Obese db/db mice, on the other hand, showed an increase in only microvascular density but this was not associated with an increase in non-FITC perfusing vessels. PA branch density was higher than controls but branch diameter was reduced. Diabetes also promoted astrogliosis. These results suggests that type 2 diabetes leads to cerebral neovascularization and remodeling but structural characteristics of newly formed vessels differ between lean and obese models that have mild or severe hyperglycemia, respectively. The prevention of dysfunctional cerebral neovascularization by early glucose control suggests that hyperglycemia is a mediator of this response. N=4-8 * p≤ 0.05, ** p≤ 0.005 *** 0.0005

Detecting a keystone species European aspen in boreal forests with airborne hyperspectral, LiDAR and UAV data with machine learning methods

2021 ◽  
Author(s):  
Timo Kumpula ◽  
Janne Mäyrä ◽  
Anton Kuzmin ◽  
Arto Viinikka ◽  
Sonja Kivinen ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Deep Learning ◽  
High Resolution ◽  
Boreal Forests ◽  
Tree Level ◽  
Support Vector ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
European Aspen

<p>Sustainable forest management increasingly highlights the maintenance of biological diversity and requires up-to-date information on the occurrence and distribution of key ecological features in forest environments. Different proxy variables indicating species richness and quality of the sites are essential for efficient detecting and monitoring forest biodiversity. European aspen (Populus tremula L.) is a minor deciduous tree species with a high importance in maintaining biodiversity in boreal forests. Large aspen trees host hundreds of species, many of them classified as threatened. However, accurate fine-scale spatial data on aspen occurrence remains scarce and incomprehensive.</p><p> </p><p>We studied detection of aspen using different remote sensing techniques in Evo, southern Finland. Our study area of 83 km<sup>2</sup> contains both managed and protected southern boreal forests characterized by Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst), and birch (Betula pendula and pubescens L.), whereas European aspen has a relatively sparse and scattered occurrence in the area. We collected high-resolution airborne hyperspectral and airborne laser scanning data covering the whole study area and ultra-high resolution unmanned aerial vehicle (UAV) data with RGB and multispectral sensors from selected parts of the area. We tested the discrimination of aspen from other species at tree level using different machine learning methods (Support Vector Machines, Random Forest, Gradient Boosting Machine) and deep learning methods (3D convolutional neural networks).</p><p> </p><p>Airborne hyperspectral and lidar data gave excellent results with machine learning and deep learning classification methods The highest classification accuracies for aspen varied between 91-92% (F1-score). The most important wavelengths for discriminating aspen from other species included reflectance bands of red edge range (724–727 nm) and shortwave infrared (1520–1564 nm and 1684–1706 nm) (Viinikka et al. 2020; Mäyrä et al 2021). Aspen detection using RGB and multispectral data also gave good results (highest F1-score of aspen = 87%) (Kuzmin et al 2021). Different remote sensing data enabled production of a spatially explicit map of aspen occurrence in the study area. Information on aspen occurrence and abundance can significantly contribute to biodiversity management and conservation efforts in boreal forests. Our results can be further utilized in upscaling efforts aiming at aspen detection over larger geographical areas using satellite images.</p>

Optimal Design of Composite Material Maintenance Structure for Aircraft Based on ANSYS Workbench

2021 ◽  
Vol 871 ◽  
pp. 216-221
Author(s):  
Jing Tao Dai ◽  
Pei Zhong Zhao ◽  
Hong Bo Su ◽  
Hao Dong Liu ◽  
Yu Bo Wang ◽  
...  
Keyword(s):  
Finite Element ◽  
Composite Material ◽  
Optimal Design ◽  
Structural Characteristics ◽  
Structural Parameters ◽  
Element Model ◽  
Composite Cement ◽  
Composite Patch ◽  
Length Width ◽  
Ansys Workbench

Composite material is widely used to maintain damaged structures of aircraft. The 3D finite element model of composite cement maintenance for aircraft is established by finite element method software ANSYS Workbench. The structural characteristics and usage status of the composite cement maintenance model is analyzed, and then the optimal structural parameters of the composite patch are obtained, including the length, width and thickness. The results show that the composite cement maintenance method could effectively restore the rigidity, and improve the strength of the structure. Furthermore, the optimal design for composite patch ensures safety of aircraft, economics of maintenance, and operability of repair methods.

Identifying and quantifying structural characteristics of heterogeneous boreal forests using laser scanner data

2005 ◽  
Vol 216 (1-3) ◽  
pp. 41-50 ◽  
Author(s):  
M. Maltamo ◽  
P. Packalén ◽  
X. Yu ◽  
K. Eerikäinen ◽  
J. Hyyppä ◽  
...  
Keyword(s):  
Boreal Forests ◽  
Structural Characteristics ◽  
Laser Scanner ◽  
Scanner Data

scholarly journals Influence of Adhesion Properties on the Crash Behavior of Steel/Polymer/Steel Sandwich Crashboxes: An Experimental Study

Metals ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1400 ◽  
Author(s):  
Mohamed Harhash ◽  
Moritz Kuhtz ◽  
Jonas Richter ◽  
Andreas Hornig ◽  
Maik Gude ◽  
...  
Keyword(s):  
Energy Absorption ◽  
Failure Modes ◽  
Structural Characteristics ◽  
Structural Parameters ◽  
Failure Behavior ◽  
Adhesion Properties ◽  
Polymer Adhesion ◽  
Strong Adhesion ◽  
Materials Used ◽  
The Impact

The energy absorption behavior of crashboxes made of steel/polymer/steel (SPS) sandwich sheets can be influenced by numerous parameters, such as the materials used, their thicknesses and stacking, and the adhesion properties between their layers. Therefore, in the present study, the impact of steel/polymer adhesion quality on the occurring failure modes of the crashboxes and the resulting energy absorptions are experimentally analyzed. For this purpose, axial crushing and three-point bending tests on double-hat and top-hat crash boxes were performed, respectively. Three levels of adhesion quality are investigated: none, weak, and strong adhesion strengths. Additionally, the structural crash properties, such as energy absorption and maximal intrusion, are determined and analyzed at both of the quasi-static and highly dynamic loading rates. The results of these investigations show that the adhesion strengths chosen here significantly influence both the failure modes and the energy absorption values. In particular, the structural parameters, in the case of no adhesion, are at most half of those in the case of strong adhesion. However, it is also shown that, in the case of weak adhesion, the structural characteristics are slightly reduced. Based on these results, the possibility to adjust the adhesion strength—globally and/or locally—could be used in future activities to purposefully tailor the failure behavior of hybrid crashboxes.

scholarly journals SAP: An IoT Application Module Placement Strategy Based on Simulated Annealing Algorithm in Edge-Cloud Computing

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Juan Fang ◽  
Kai Li ◽  
Juntao Hu ◽  
Xiaobin Xu ◽  
Ziyi Teng ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Simulated Annealing ◽  
Energy Consumption ◽  
Simulated Annealing Algorithm ◽  
Smart Cities ◽  
Structural Characteristics ◽  
Edge Computing ◽  
The Internet ◽  
Sensors And Actuators ◽  
Application Module

The Internet of Things (IoT) is rapidly growing and provides the foundation for the development of smart cities, smart home, and health care. With more and more devices connecting to the Internet, huge amounts of data are produced, creating a great challenge for data processing. Traditional cloud computing has the problems of long delays. Edge computing is an extension of cloud computing, processing data at the edge of the network can reduce the long processing delay of cloud computing. Due to the limited computing resources of edge servers, resource management of edge servers has become a critical research problem. However, the structural characteristics of the subtask chain between each pair of sensors and actuators are not considered to address the task scheduling problem in most existing research. To reduce processing latency and energy consumption of the edge-cloud system, we propose a multilayer edge computing system. The application deployed in the system is based on directed digraph. To fully use the edge servers, we proposed an application module placement strategy using Simulated Annealing module Placement (SAP) algorithm. The modules in an application are bounded to each sensor. The SAP algorithm is designed to find a module placement scheme for each sensor and to generate a module chain including the mapping of the module and servers for each sensor. Thus, the edge servers can transmit the tuples in the network with the module chain. To evaluate the efficacy of our algorithm, we simulate the strategy in iFogSim. Results show the scheme is able to achieve significant reductions in latency and energy consumption.

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