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At least 163 records · Page 9

Geometric Analysis Based Double Closed-loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process

In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a RBF neural network (NN) with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop sysyem, a geometric analysis based ILC method is adopted in the outer loop. Lastly, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach.

42 ENGINEERING↗

Ensemble Estimation of Historical Evapotranspiration for the Conterminous U.S.

Abstract Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall‐to‐wall explanatory variable maps to generate CONUS‐wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national‐scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

Environmental Sciences & Ecology↗

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Taylor, Patrick C.↗

Pros, Cons, and Alternatives to Weight Based Cost Estimating

Many cost estimating tools use weight as a major parameter in projecting the cost. This is often combined with modifying factors such as complexity, technical maturity of design, environment of operation, etc. to increase the fidelity of the estimate. For a set of conceptual designs, all meeting the same requirements, increased weight can be a major driver in increased cost. However, once a design is fixed, increased weight generally decreases cost, while decreased weight generally increases cost - and the relationship is not linear. Alternative approaches to estimating cost without using weight (except perhaps for materials costs) have been attempted to try to produce a tool usable throughout the design process - from concept studies through development. This paper will address the pros and cons of using weight based models for cost estimating, using liquid rocket engines as the example. It will then examine approaches that minimize the imp~ct of weight based cost estimating. The Rocket Engine- Cost Model (RECM) is an attribute based model developed internally by Pratt & Whitney Rocketdyne for NASA. RECM will be presented primarily to show a successful method to use design and programmatic parameters instead of weight to estimate both design and development costs and production costs. An operations model developed by KSC, the Launch and Landing Effects Ground Operations model (LLEGO), will also be discussed.

Joyner, Claude R.↗

Will weight loss cause significant dosimetric changes of target volumes and organs at risk in nasopharyngeal carcinoma treated with intensity-modulated radiation therapy?

This study aimed to quantify dosimetric effects of weight loss for nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiation therapy (IMRT). Overall, 25 patients with NPC treated with IMRT were enrolled. We simulated weight loss during IMRT on the computer. Weight loss model was based on the planning computed tomography (CT) images. The original external contour of head and neck was labeled plan 0, and its volume was regarded as pretreatment normal weight. We shrank the external contour with different margins (2, 3, and 5 mm) and generated new external contours of head and neck. The volumes of reconstructed external contours were regarded as weight during radiotherapy. After recontouring outlines, the initial treatment plan was mapped to the redefined CT scans with the same beam configurations, yielding new plans. The computer model represented a theoretical proportional weight loss of 3.4% to 13.7% during the course of IMRT. The dose delivered to the planning target volume (PTV) of primary gross tumor volume and clinical target volume significantly increased by 1.9% to 2.9% and 1.8% to 2.9% because of weight loss, respectively. The dose to the PTV of gross tumor volume of lymph nodes fluctuated from −2.0% to 1.0%. The dose to the brain stem and the spinal cord was increased (p < 0.001), whereas the dose to the parotid gland was decreased (p < 0.001). Weight loss may lead to significant dosimetric change during IMRT. Repeated scanning and replanning for patients with NPC with an obvious weight loss may be necessary.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A new gravitational model for the earth from satellite tracking data - GEM-T1

A computation of a terrestrial gravitational field model called the Goddard Earth Model GEM-T1 is discussed and compared to previous models, including the GEM-L2. The software tools were redesigned for the model, allowing for the optimization of the technique of relative data weighting and model estimation used in GEM solutions. The GEM-T1 model provides a simultaneous solution for a gravity model in spherical harmonics complete to degree and order 36, a subset of 66 ocean tidal coefficients for the long-wavelength components of 12 major tides, and 5-day averaged earth rotation and polar motion parameters for the 1980 period on. GEM-T1 was derived from satellite tracking data acquired on 17 different satellites whose inclinations ranged from 15 degrees to polar. A simulation of the TOPEX/POSEIDON orbit using the covariances of the GEM-T1 model was made. Estimated radial error for the simulation was reduced to less than 30 cm rms.

Marsh, J. G.↗

SU-G-JeP3-04: Estimating 4D CBCT from Prior Information and Extremely Limited Angle Projections Using Structural PCA and Weighted Free-Form Deformation

Purpose: To investigate the feasibility of using structure-based principal component analysis (PCA) motion-modeling and weighted free-form deformation to estimate on-board 4D-CBCT using prior information and extremely limited angle projections for potential 4D target verification of lung radiotherapy. Methods: A technique for lung 4D-CBCT reconstruction has been previously developed using a deformation field map (DFM)-based strategy. In the previous method, each phase of the 4D-CBCT was generated by deforming a prior CT volume. The DFM was solved by a motion-model extracted by global PCA and a free-form deformation (GMM-FD) technique, using data fidelity constraint and the deformation energy minimization. In this study, a new structural-PCA method was developed to build a structural motion-model (SMM) by accounting for potential relative motion pattern changes between different anatomical structures from simulation to treatment. The motion model extracted from planning 4DCT was divided into two structures: tumor and body excluding tumor, and the parameters of both structures were optimized together. Weighted free-form deformation (WFD) was employed afterwards to introduce flexibility in adjusting the weightings of different structures in the data fidelity constraint based on clinical interests. XCAT (computerized patient model) simulation with a 30 mm diameter lesion was simulated with various anatomical and respirational changes from planning 4D-CT to onboard volume. The estimation accuracy was evaluated by the Volume-Percent-Difference (VPD)/Center-of-Mass-Shift (COMS) between lesions in the estimated and “ground-truth” on board 4D-CBCT. Results: Among 6 different XCAT scenarios corresponding to respirational and anatomical changes from planning CT to on-board using single 30° on-board projections, the VPD/COMS for SMM-WFD was reduced to 10.64±3.04%/1.20±0.45mm from 21.72±9.24%/1.80±0.53mm for GMM-FD. Using 15° orthogonal projections, the VPD/COMS was further reduced to 1.91±0.86%/0.31±0.42mm based on SMM-WFD. Conclusion: Compared to GMM-FD technique, the SMM-WFD technique can substantially improve the 4D-CBCT estimation accuracy using extremely small scan angles to provide ultra-fast 4D verification. This work was supported by the National Institutes of Health under Grant No. R01-CA184173 and a research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

Slushy weightings for the optimal pilot model

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Dillow, J. D.↗

Lipid droplets fusion in adipocyte differentiated 3T3-L1 cells: A Monte Carlo simulation

Several human worldwide diseases like obesity, type 2 diabetes, hepatic steatosis, atherosclerosis and other metabolic pathologies are related to the excessive accumulation of lipids in cells. Lipids accumulate in spherical cellular inclusions called lipid droplets (LDs) whose sizes range from fraction to one hundred of micrometers in adipocytes. It has been suggested that LDs can grow in size due to a fusion process by which a larger LD is obtained with spherical shape and volume equal to the sum of the progenitors’ ones. In this study, the size distribution of two populations of LDs was analyzed in immature and mature (5-days differentiated) 3T3-L1 adipocytes (first and second populations, respectively) after Oil Red O staining. A Monte Carlo simulation of interaction between LDs has been developed in order to quantify the size distribution and the number of fusion events needed to obtain the distribution of the second population size starting from the first one. Four models are presented here based on different kinds of interaction: a surface weighted interaction (R2 Model), a volume weighted interaction (R3 Model), a random interaction (Random model) and an interaction related to the place where the LDs are born (Nearest Model). The last two models mimic quite well the behavior found in the experimental data. This work represents a first step in developing numerical simulations of the LDs growth process. Due to the complex phenomena involving LDs (absorption, growth through additional neutral lipid deposition in existing droplets, de novo formation and catabolism) the study focuses on the fusion process. The results suggest that, to obtain the observed size distribution, a number of fusion events comparable with the number of LDs themselves is needed. Moreover the MC approach results a powerful tool for investigating the LDs growth process. Highlights: • We evaluated the role of the fusion process in the synthesis of the lipid droplets. • We compared the size distribution of the lipid droplets in immature and mature cells. • We used the Monte Carlo simulation approach, simulating 10 thousand of fusion events. • Four different interaction models between the lipid droplets were tested. • The best model which mimics the experimental measures was selected.

60 APPLIED LIFE SCIENCES↗

TH-A-9A-04: Incorporating Liver Functionality in Radiation Therapy Treatment Planning

Purpose: Liver SBRT patients have both variable pretreatment liver function (e.g., due to degree of cirrhosis and/or prior treatments) and sensitivity to radiation, leading to high variability in potential liver toxicity with similar doses. This work aims to explicitly incorporate liver perfusion into treatment planning to redistribute dose to preserve well-functioning areas without compromising target coverage. Methods: Voxel-based liver perfusion, a measure of functionality, was computed from dynamic contrast-enhanced MRI. Two optimization models with different cost functions subject to the same dose constraints (e.g., minimum target EUD and maximum critical structure EUDs) were compared. The cost functions minimized were EUD (standard model) and functionality-weighted EUD (functional model) to the liver. The resulting treatment plans delivering the same target EUD were compared with respect to their DVHs, their dose wash difference, the average dose delivered to voxels of a particular perfusion level, and change in number of high-/low-functioning voxels receiving a particular dose. Two-dimensional synthetic and three-dimensional clinical examples were studied. Results: The DVHs of all structures of plans from each model were comparable. In contrast, in plans obtained with the functional model, the average dose delivered to high-/low-functioning voxels was lower/higher than in plans obtained with its standard counterpart. The number of high-/low-functioning voxels receiving high/low dose was lower in the plans that considered perfusion in the cost function than in the plans that did not. Redistribution of dose can be observed in the dose wash differences. Conclusion: Liver perfusion can be used during treatment planning potentially to minimize the risk of toxicity during liver SBRT, resulting in better global liver function. The functional model redistributes dose in the standard model from higher to lower functioning voxels, while achieving the same target EUD and satisfying dose limits to critical structures. This project is funded by MCubed and grant R01-CA132834.

60 APPLIED LIFE SCIENCES↗

SciDAC Center for Gyrokinetic Particle Simulation of Turbulent Transport in Burning Plasmas

During the first year of the SciDAC gyrokinetic particle simulation (GPS) project, the GPS team (Zhihong Lin, Liu Chen, Yasutaro Nishimura, and Igor Holod) at the University of California, Irvine (UCI) studied the tokamak electron transport driven by electron temperature gradient (ETG) turbulence, and by trapped electron mode (TEM) turbulence and ion temperature gradient (ITG) turbulence with kinetic electron effects, extended our studies of ITG turbulence spreading to core-edge coupling. We have developed and optimized an elliptic solver using finite element method (FEM), which enables the implementation of advanced kinetic electron models (split-weight scheme and hybrid model) in the SciDAC GPS production code GTC. The GTC code has been ported and optimized on both scalar and vector parallel computer architectures, and is being transformed into objected-oriented style to facilitate collaborative code development. During this period, the UCI team members presented 11 invited talks at major national and international conferences, published 22 papers in peer-reviewed journals and 10 papers in conference proceedings. The UCI hosted the annual SciDAC Workshop on Plasma Turbulence sponsored by the GPS Center, 2005-2007. The workshop was attended by about fifties US and foreign researchers and financially sponsored several gradual students from MIT, Princeton University, Germany, Switzerland, and Finland. A new SciDAC postdoc, Igor Holod, has arrived at UCI to initiate global particle simulation of magnetohydrodynamics turbulence driven by energetic particle modes. The PI, Z. Lin, has been promoted to the Associate Professor with tenure at UCI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Simulated Wake Characteristics Data for Closely Spaced Parallel Runway Operations Analysis

A simulation experiment was performed to generate and compile wake characteristics data relevant to the evaluation and feasibility analysis of closely spaced parallel runway (CSPR) operational concepts. While the experiment in this work is not tailored to any particular operational concept, the generated data applies to the broader class of CSPR concepts, where a trailing aircraft on a CSPR approach is required to stay ahead of the wake vortices generated by a lead aircraft on an adjacent CSPR. Data for wake age, circulation strength, and wake altitude change, at various lateral offset distances from the wake-generating lead aircraft approach path were compiled for a set of nine aircraft spanning the full range of FAA and ICAO wake classifications. A total of 54 scenarios were simulated to generate data related to key parameters that determine wake behavior. Of particular interest are wake age characteristics that can be used to evaluate both time- and distance- based in-trail separation concepts for all aircraft wake-class combinations. A simple first-order difference model was developed to enable the computation of wake parameter estimates for aircraft models having weight, wingspan and speed characteristics similar to those of the nine aircraft modeled in this work.

Guerreiro, Nelson M.↗

Aggregation of Leslie matrix models with application to ten diverse animal species

Some grouping is necessary when constructing a Leslie matrix model because it involves discretizing a continuous process of births and deaths. Here, the level of grouping is determined by the number of age classes and frequency of sampling. It is largely unknown what is lost or gained by using fewer age classes, and I address this question using aggregation theory. I derive an aggregator for a Leslie matrix model using weighted least squares, determine what properties an aggregated matrix inherits from the original matrix, evaluate aggregation error, and measure the influence of aggregation on asymptotic and transient behaviors. To gauge transient dynamics, I employ reactivity of the standardized Leslie matrix. I apply the aggregator to 10 Leslie models developed for animal populations drawn from a diverse set of species. Several properties are inherited by the aggregated matrix: (a) it is a Leslie matrix; (b) it is irreducible whenever the original matrix is irreducible; (c) it is primitive whenever the original matrix is primitive; and (d) its stable population growth rate and stable age distribution are consistent with those of the original matrix if the least squares weights are equal to the original stable age distribution. In the application, depending on the population modeled, when the least squares weights do not follow the stable age distribution, the stable population growth rate of the aggregated matrix may or may not be approximately consistent with that of the original matrix. Transient behavior is lost with high aggregation.

54 ENVIRONMENTAL SCIENCES↗

An Investigation of the Wear Performance of Aged Inconel 718 Superalloy by the Fuzzy Logic Approach

In this study, the effects of δ, γ′ and γ″ phases on the microstructure and wear behavior of Inconel 718 alloy, produced by powder metallurgy technique, were analyzed experimentally and a fuzzy logic model was developed for the weight loss prediction after the wear tests. Aging process was carried out in two stages: firstly at 720 °C for 8 h and then at 620 °C for 6-10 h. Wear tests were performed at five different sliding distances (400-2000 m) for 1 ms{sup −1} sliding speed under 30 to 60 N loads. Weight loss prediction model was developed by using fuzzy logic method. SEM images of Inconel 718 alloy aged for 6, 8 and 10 h at 620 °C show intermetallic precipitates formed around particle boundaries. XRD examinations showed orthorhombic δ (Ni{sub 3}Nb), BCT γ″ (Ni{sub 3}Nb), FCC γ′ Ni{sub 3}(Al,Ti) hexagonal Laves (Fe{sub 2}Nb) phases formed in the structure with the same chemical composition and different crystal lattice. Accurate estimates were obtained in the developed fuzzy logic model. It was illustrated that this fuzzy logic model can be used successfully for the prediction of weight loss in wear tests of Inconel 718 alloy that was produced by powder metallurgy method.

36 MATERIALS SCIENCE↗

COOLR: A New System for Dynamic Thermal-Aware Computing

Extreme-scale systems need to walk a fine line between the amount of cooling they receive and the thermal-induced performance and reliability degradation they can sustain. System managers are extremely motivated to battle cooling-energy cost: the largest line item in their total operating cost. On the other hand, pushing the nodes to peak performance in tightened cooling regimes places the burden on the dynamic thermal management (DTM) to protect the hardware. DTM schemes throttle performance to relieve heat accumulation within nodes when cooling cannot mitigate the problem. These interventions prevent fatal failures but introduce inevitable performance degradations and variations. Such variations can have drastic consequences on the performance of extreme-scale systems. Furthermore, distribution of heat across different system nodes depends not only on the amount of workload. Even if a strictly equal share of computational load is assigned to all nodes, there are physical attributes and topological features of each system that inherently cause uneven accumulation of heat. These can cause one subcomponent to trigger DTM prematurely and penalize the overall system. Our goal in this project is to create a holistic thermal-aware view of the system, capturing both inherent physical attributes and dynamic system state. We developed COOLR, a dynamic system with the ability to evaluate the interplay between management of computation, data, power dissipation, and thermal state. Thereby, COOLR will achieve higher overall performance at the same energy and cooling cost. First, we performed a systematic power and thermal modeling and of high performance computing architectures. Analytical and empirical techniques were blended to generate a light-weight thermal model of target systems. Second, we developed a thermal-aware OS and runtime system. Policies for managing resources and schedules for processes has been designed to co-optimize the thermal state and performance of the system. The main outcome of our proposed thermal-aware dynamic computing system are scheduling and allocation of processes and memory accesses leading to an appropriately “skewed” distribution of activity across the system. The ultimate result of this new arrangement resulted in reduced occurrences of hotspots and reduced episodes of DTM intervention, leading to improvements in performance. The overall thermal characterization and modeling methodology (thermal instrumentation techniques, model building, and systematic model reduction) resulting from this project can be applied to systems beyond our immediate scope and will be applicable to future scaling. The thermal-aware dynamic computing paradigm will impact the efficiency of extreme-scale systems. The gained “thermal slack” can be given back to further tighten the cooling budget, benefiting the management cost of next generation extreme-scale systems.

97 MATHEMATICS AND COMPUTING↗

Optimal Methods for Estimating Cactus Pear Biomass Using Cladode Dimensions of Morphologically Diverse Accessions

Current allometric methods for photosynthetic-stem (cladode) plants, such as cactus pear (Opuntia spp.), require refinement to be used in field settings in which diverse accessions are grown. We analysed cladode dimensional data using 14 accessions representing four species and two hybrids to quantify statistically significant morphological differences among accessions and derived cross-accession models to approximate cladode fresh weight. A Box model using cladode dimensions (e.g., length, width, thickness and diameter) and factorial combinations of these measures (e.g., length*width*thickness*diameter vs. fresh weight) resulted in the highest coefficient of determination (R 2 = 0.95 general fit) across all accessions for estimating fresh weight along with parsimony estimates using the Schwarz–Bayes Criterion (SBC), which assesses the most consistent performance on individual accessions. A Fitting-box modelling approach used the measured cladode area captured using ImageJ (R 2 = 0.93 general fit). Lastly, an Elliptical model used an elliptical approximation for the measured area and performed well over all accessions (R 2 = 0.94 general fit) while avoiding extensive manual measurements. These models meet or exceed the performance of previously published approaches when applied across morphologically diverse accessions, providing efficient tools for nondestructive estimation of cactus pear biomass under the conditions tested.

Opuntia↗

Development of LACIE CCEA-1 weather/wheat yield models

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

Strommen, N. D.↗

Abundance patterns in the interstellar medium of early-type galaxies observed with Suzaku

We have analyzed 17 early-type galaxies, 13 ellipticals and 4 S0 galaxies, observed with Suzaku, and investigated metal abundances (O, Mg, Si, and Fe) and abundance ratios (O/Fe, Mg/Fe, and Si/Fe) in the interstellar medium (ISM). The emission from each on-source region, which is four times the effective radius, r {sub e}, is reproduced with one-temperature (1T) or two-temperature (2T) thermal plasma models as well as a multi-temperature model, using APEC plasma code version 2.0.1. The multi-temperature model gave almost the same abundances and abundance ratios with the 1T or 2T models. The weighted averages of the O, Mg, Si, and Fe abundances of all the sample galaxies derived from the multi-temperature model fits are 0.83 ± 0.04, 0.93 ± 0.03, 0.80 ± 0.02, and 0.80 ± 0.02 solar, respectively, in solar units according to the solar abundance table by Lodders in 2003. These abundances show no significant dependence on the morphology and environment. The systematic differences in the derived metal abundances between versions 2.0.1 and 1.3.1 of the APEC plasma codes were investigated. The derived O and Mg abundances in the ISM agree with the stellar metallicity within an aperture with a radius of one r {sub e} derived from optical spectroscopy. From these results, we discuss the past and present Type Ia supernova rates and star formation histories in early-type galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗