A statistical methodology was applied to the simultaneous calibration and validation of thermodynamic models for the uptake of CO{sub 2} in mesoporous silica-supported amines. The methodology is Bayesian, and follows the procedure introduced by Kennedy and O'Hagan. One key aspect of the application presented is the use of quantum chemical calculations to define prior probability distributions for physical model parameters. Inclusion of this prior information proved to be crucial to the identifiability of model parameters against experimental thermogravimetric data. Through the statistical analysis, a quantitative assessment of the accuracy of various quantum chemical methods is produced. Another important aspect of the current approach is the conditioning of the model form discrepancy – a critical component of the Kennedy and O'Hagan methodology – to the experimental data in such a manner that it becomes an implicit function of the model parameters and thereby connected with the posterior distribution. It is shown that the inclusion of prior information in the analysis leads to a shifting of uncertainty from the posterior distribution for model parameters to this conditioned model form discrepancy. Prospects for more accurate model predictions and propagation of uncertainty in upscaling and extrapolation through a “model-plus-discrepancy” approach are discussed. The synthesis methods and thermogravimetric characterization of hybrid grafted/impregnated mesoporous silica-supported amine sorbents are presented, along with the details of the quantum chemical study, which shows that a carbamic acid–base acceptor complex is the most stable form of adsorbed CO{sub 2} in both alkanol- and ethyleneamines.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Factors Predictive of Symptomatic Radiation Injury After Linear Accelerator-Based Stereotactic Radiosurgery for Intracerebral Arteriovenous Malformations

Purpose: To investigate predictive factors in the development of symptomatic radiation injury after treatment with linear accelerator-based stereotactic radiosurgery for intracerebral arteriovenous malformations and relate the findings to the conclusions drawn by Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC). Methods and Materials: Archived plans for 73 patients who were treated at the British Columbia Cancer Agency were studied. Actuarial estimates of freedom from radiation injury were calculated using the Kaplan-Meier method. Univariate and multivariate Cox proportional hazards models were used for analysis of incidence of radiation injury. Log-rank test was used to search for dosimetric parameters associated with freedom from radiation injury. Results: Symptomatic radiation injury was exhibited by 14 of 73 patients (19.2%). Actuarial rate of symptomatic radiation injury was 23.0% at 4 years. Most patients (78.5%) had mild to moderate deficits according to Common Terminology Criteria for Adverse Events, version 4.0. On univariate analysis, lesion volume and diameter, dose to isocenter, and a V{sub x} for doses {>=}8 Gy showed statistical significance. Only lesion diameter showed statistical significance (p < 0.05) in a multivariate model. According to the log-rank test, AVM volumes >5 cm{sup 3} and diameters >30 mm were significantly associated with the risk of radiation injury (p < 0.01). The V{sub 12} also showed strong association with the incidence of radiation injury. Actuarial incidence of radiation injury was 16.8% if V{sub 12} was <28 cm{sup 3} and 53.2% if >28 cm{sup 3} (log-rank test, p = 0.001). Conclusions: This study confirms that the risk of developing symptomatic radiation injury after radiosurgery is related to lesion diameter and volume and irradiated volume. Results suggest a higher tolerance than proposed by QUANTEC. The widely differing findings reported in the literature, however, raise considerable uncertainties.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2012

A One-Dimensional (1-D) Three-Region Model for a Bubbling Fluidized-Bed Adsorber

A general one-dimensional (1-D), three-region model for a bubbling fluidized-bed adsorber with internal heat exchangers has been developed. The model can predict the hydrodynamics of the bed and provides axial profiles for all temperatures, concentrations, and velocities. The model is computationally fast and flexible and allows for any system of adsorption and desorption reactions to be modeled, making the model applicable to any adsorption process. The model has been implemented in both gPROMS and Aspen Custom Modeler, and the behavior of the model has been verified.

36 MATERIALS SCIENCE↗

DOE OSTI2011

The correlation of tissue motion within the lung: implications on fiducial based treatments

In radiation therapy many motion management and alignment techniques rely on the accuracy of an internal fiducial acting as a surrogate for target motion within the lung. Although fiducials are routinely used as surrogates for tumor motion, the extent to which varying spatial locations in the lung move similarly to other locations has yet to be quantitatively analyzed. In an attempt to analyze the motion correlation throughout the lung, ten primary lung cancer patients underwent IRB-approved 4DCT scans in the supine position. Deformable registration produced motion vectors for each voxel between exhalation and inhalation. Modeling was performed for each vector and all surrounding vectors within the lung in order to determine the mean 3D Euclidean distance necessary for an implanted fiducial to correlate with surrounding tissue motion to within 3 mm (left lower: 1.7 cm, left upper: 2.1 cm, right lower 1.6 cm, and right upper 2.9 cm). No general implantation rule of where to position a fiducial with respect to the tumor was found as the motion is highly patient and lobe specific. Correlation maps are presented showcasing spatial anisotropy of the motion of tissue surrounding the tumor.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS1990

Optical neural network system for pose determination of spinning satellites

An optical neural network architecture and algorithm based on a Hopfield optimization network are presented for multitarget tracking. This tracker utilizes a neuron for every possible target track, and a quadratic energy function of neural activities which is minimized using gradient descent neural evolution. The neural net tracker is demonstrated as part of a system for determining position and orientation (pose) of spinning satellites with respect to a robotic spacecraft. The input to the system is time sequence video from a single camera. Novelty detection and filtering are utilized to locate and segment novel regions from the input images. The neural net multitarget tracker determines the correspondences (or tracks) of the novel regions as a function of time, and hence the paths of object (satellite) parts. The path traced out by a given part or region is approximately elliptical in image space, and the position, shape and orientation of the ellipse are functions of the satellite geometry and its pose. Having a geometric model of the satellite, and the elliptical path of a part in image space, the three-dimensional pose of the satellite is determined. Digital simulation results using this algorithm are presented for various satellite poses and lighting conditions.

Lee, Andrew↗