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Forest Ecosystem Monitoring Using Unmanned Aerial Systems
Published in David R. Green, Billy J. Gregory, Alex R. Karachok, Unmanned Aerial Remote Sensing, 2020
Cristina Gómez, Tristan R.H. Goodbody, Nicholas C. Coops, Flor Álvarez-Taboada, Enoc Sanz-Ablanedo
Goodbody et al. (2017b) found these linear regression models accurate and effective for estimation of attributes. The DAP model for volume had an R2 of 0.93 (Figure 11.3) and included three metrics describing height (90th percentile of height), canopy cover (cover >2 m), and cross-sectional density (mean height between 10 and 20 m). The application of linear models wall-to-wall allowed for the creation of maps that describe the spatial distribution of stem volume across the operation area (Figure 11.3, inset). Visual comparisons between the DAP CHM shown in Figure 11.4 and the wall-to-wall volume map in Figure 11.3 confirm that the volume models were accurate at delineating the location of harvest and representing residual volume.
Absolute and Reference Dosimetry
Published in Harald Paganetti, Proton Therapy Physics, 2018
For scanned proton beams, however, dose calculations are based on a superposition of a large number of narrow beam spots, and the dose calculation and optimization are based on the number of particles in each spot. The relevant quantity is either particle number, related to fluence, or its dosimetric equivalent, dose-area-product (DAP). While the direct measurement of particle number appears very attractive since it is relatively straightforward and is directly related to the quantity used by the treatment planning system to define the relative weights of beam spots, it must be realized that, in the dose calculation, the fluence has to be multiplied with the mass stopping power of water (or tissue) that has a considerable uncertainty, given the uncertainty on the stopping power data themselves and the uncertainty on the exact spectrum of charged particles at the measurement depth (primary protons + secondary charged particles produced in nuclear interactions and target fragmentation). As will be explained in Section 10.3.4, using dose-based or DAP based approaches, the experimentally determined DAP has to be divided by the DAP per incident proton (sometimes also called the mean stopping power per unit of incident proton fluence) to derive the number of particles in a spot. The uncertainty on this divider is evenly large as the mass stopping power, but since it is highly correlated with the DAP per incident proton or the mean stopping power per unit of incident proton fluence with which the fluence is multiplied in the dose calculation, this results in a cancelation of most of the uncertainty contribution. This argument favors calibration in terms of DAP rather than particle number.
Thermoset/Thermoplastic Blends with a Crosslinked Thermoplastic Network Matrix
Published in Boris A. Rozenberg, Grigori M. Sigalov, Marina Z. Aldoshina, Yurii B. Scheck, Heterophase Network Polymers, 2020
Ying Yang, Tsuneo Chiba, Takashi Inoue
Figure 8 shows FT-IR spectra of DAP/PPE/PBP 80/20/1.75 at various cure times. A 3020 cm-1 band is assigned to C–H stretching vibration in the vinyl group of DAP. It decreases with cure and eventually disappears, suggesting simply the polymerization of DAP. A 2923 cm-1 band is assigned to the stretching vibration of C–H in −CH2− and methyl groups attached to a phenyl ring. It increases with cure, suggesting the graft reaction of DAP on the methyl group of PPE. The grafting is expected to generate two C–H bonds by consuming one C-H bond of the PPE methyl group and one C=C double bond of DAP.
Vulnerability of asymmetric multi-storey buildings in the context of performance-based seismic design
Published in European Journal of Environmental and Civil Engineering, 2021
Mohammed Hentri, Miloud Hemsas, Djamel Nedjar
The first step of the procedure consists of the development of a 3D model of the building (Figure 5(a)), in which the non-linear monotonic behaviour of the materials is perfectly defined using fibre elements discretisation. For this model, the element is discretised into longitudinal steel and concrete fibres such that the section force–deformation relation is derived by integration of the stress–strain relation of the fibres (see Figure 3). Afterwards, a DAP is performed to a non-linear model of the structure and the result capacity curves of the MDOF system (Figure 5(b)) is transformed thereafter to equivalent SDOF model based on the current deformed pattern of the structure (Figure 5(c,d)). Displacement contributions of several modes are combined (with a SRSS combination rule) and then incrementally applied to the structure. The DAP algorithm is described and discussed in great detail in Pinho and Antoniou (2005).
Joint capacity, inventory, and demand allocation decisions in manufacturing systems
Published in IISE Transactions, 2019
Vedat Bayram, Fatma Gzara, Samir Elhedhli
In this section, we compare models DAP-D and DAP-D-Exact for different values of n, m, λ, ρ, and c, where is the capacity utilization level. Tables 1 and 2 report the average savings in total cost and the average CPU time, where τ is a parameter that is used to scale down c, i.e., . Therefore, we report two cost improvement percentages: “% Imp.1” and “% Imp.2”, denoting the cost savings of DAP-D-Exact compared with “Opt.Cost” and “Cost”, respectively, where “Opt.Cost” is the optimal cost achieved by solving model DAP-D and “Cost” refers to the cost of DAP-D with base-stock levels . Not only is DAP-D-Exact faster to solve than DAP-D in almost all instances, but also the solution times of DAP-D seem to deteriorate depending on the problem parameters whereas DAP-D-Exact is hardly affected.
Fabrication and drag reduction of superhydrophobic surface on steel substrates
Published in Surface Engineering, 2018
Haifeng Zhang, Yanjing Tuo, Qingchun Wang, Bingjie Jin, Liang Yin, Xiaowei Liu
The CAs and SAs are used to define the wettability, which is an important property of a superhydrophobic surface. To evaluate the wettability of the as-prepared samples, the CAs and SAs were measured using a water droplet of 4–5 μL. Here, we measured the CAs and SAs of samples that grew in DAP solution of different concentrations. As shown in Figure 4, the CAs of the as-prepared surfaces are higher than 150° after fluorination. When the concentration of DAP solution is 20 mM L−1, the as-prepared surface has the largest CA (164.9°) and the lowest SA (2.3°). In addition, the surface exerts no apparent adhesive force on the suspended droplet.