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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A cross-sectional study of the temporal evolution of electricity consumption of six commercial buildings

Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged- Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15- minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Controlling radioisotope proportions when randomly sampling from Dirichlet distributions in PyRIID

As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

SU-E-J-83: Ion Imaging to Better Estimate In-Vivo Relative Stopping Powers Using X-Ray CT Prior-Knowledge Information

Purpose: To reduce uncertainties in relative stopping power (RSP) estimates for ions (alpha and carbon) by using Ion radiographic-imaging and X-ray CT prior-knowledge. Methods: A 36×36 phantom matrix composed of 9 materials with different thicknesses and randomly placed is generated. Theoretical RSPs are calculated using stopping power (SP) data from three references (Janni, ICRU49 and Bischel). We introduced an artificial systematic error (1.5%, 2.5% or 3.5%) and a random error (<0.5%) to the SP to simulated patient ion-range errors present in clinic environment. Carbon/alpha final energy for each RSPs set (theoretical and from CT images) is obtained with a ray-tracing algorithm. A gradient descent (GD) method is used to minimize the difference in exit particle energy, between theory and X-ray CT RSP maps, by iteratively correcting the RSP map from X-ray CT. Once a new set of RSPs is obtained for a direction a new optimization is done over other direction using the RSPs from the previous optimization. Theoretical RSPs are compared with experimental RSPs obtained with Gammex Phantom. Results: Preliminary results show that optimized RSP values can be obtained with smaller uncertainties (<1%) than clinical RSPs (1.5% to 3.5%). Theoretical values from three different references show uncertainties, up to 3% from experimental values. Further investigation will consider prior-knowledge from RSP obtained with CT images and ion radiographies from Monte Carlo Simulations. Conclusion: GD and ray-tracing methods have been implemented to reduce RSP uncertainties from values obtained for clinical treatment. Experimental RSPs will be obtained using carbon/alpha beams to consider the existence of material dependent systematic errors. Based on the results, it is hoped to show that using ray-tracing optimization with ion radiography and prior knowledge on RPSs, treatment planning accuracy and cost-effectiveness can be improved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Device-scale CFD study for mass transfer coefficient and effective mass transfer area in packed column

Carbon dioxide (CO 2 ) is a significant contributor of greenhouse gases emissions responsible for global warming. The fossil-fueled power plant is one of the major sources of CO 2 emission worldwide and needs to be mitigated. Post-combustion carbon capture by chemical absorption can be a promising technology to reduce CO 2 emission from power plants. The absorption is carried out via countercurrent flow in the packed columns. Although monoethanolamine (MEA) is a popular solvent, it has also limitations such as high volatility of solvent, corrosivity that leads to product degradation and damage to apparatuses, low CO 2 loading capacity, etc. Therefore, alternate solvents are being explored as prospective materials for carbon capture. A water-lean solvent, CO 2 binding organic liquids (CO2BOL), is currently being developed as a prospective material in carbon capture at the Pacific Northwest National Laboratory. Since the development of the material is at the primitive stage, it needs extensive investigation before industrial deployments. Hydrodynamics and mass transfer phenomena in the packed column using CO 2 BOL is unknown. Computational fluid dynamics (CFD) can be a useful tool to understand these phenomena in the packed column. Before employing the extensive CFD investigations, one needs to carefully validate CFD predictions for accurate flow predictions. This report demonstrates the validation of multiphase flow simulations against the experimental results for both structured and random packed columns. The reactive multiphase flow simulations using volume of fluid method were conducted at a wide range of liquid loads and contacts angles. The effective area is one of the critical factors dictating interphase mass transfer due to chemical reactions. Accordingly, CFD-predicted effective areas were compared with the experimental results of Tsai et al. [1] for Mellapak 250.Y structured packing. Both results matched well at different liquid loads in the presence of fast chemical kinetics using caustic solvents. Further, reactive multiphase flow simulations were also conducted in pall ring random packing to compute effective areas in the presence of fast chemical reactions. The CFD-predicted effective area compared well with correlation developed by Song et al. [2]. With successful validations, the current simulation framework can be further used for prediction of hydrodynamics and mass transfer phenomena using CO 2 BOL solvents in the packed column. Subsequently, it would be helpful in design optimization of a packed column. In addition to validation of the CFD model, this report also explains the mechanism for enhanced liquid side mass transfer for a structured packed column as compared to the wetted wall column.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2014

Long-Term Results of a Randomized Trial in Locally Advanced Rectal Cancer: No Benefit From Adding a Brachytherapy Boost

Purpose/Objective(s): Mature data on tumor control and survival are presented from a randomized trial of the addition of a brachytherapy boost to long-course neoadjuvant chemoradiation therapy (CRT) for locally advanced rectal cancer. Methods and Materials: Between March 2005 and November 2008, 248 patients with T3-4N0-2M0 rectal cancer were prospectively randomized to either long-course preoperative CRT (50.4 Gy in 28 fractions, per oral tegafur-uracil and L-leucovorin) alone or the same CRT schedule plus a brachytherapy boost (10 Gy in 2 fractions). The primary trial endpoint was pathologic complete response (pCR) at the time of surgery; secondary endpoints included overall survival (OS), progression-free survival (PFS), and freedom from locoregional failure. Results: Results for the primary endpoint have previously been reported. This analysis presents survival data for the 224 patients in the Danish part of the trial. In all, 221 patients (111 control arm, 110 brachytherapy boost arm) had data available for analysis, with a median follow-up time of 5.4 years. Despite a significant increase in tumor response at the time of surgery, no differences in 5-year OS (70.6% vs 63.6%, hazard ratio [HR] = 1.24, P=.34) and PFS (63.9% vs 52.0%, HR=1.22, P=.32) were observed. Freedom from locoregional failure at 5 years were 93.9% and 85.7% (HR=2.60, P=.06) in the standard and in the brachytherapy arms, respectively. There was no difference in the prevalence of stoma. Explorative analysis based on stratification for tumor regression grade and resection margin status indicated the presence of response migration. Conclusions: Despite increased pathologic tumor regression at the time of surgery, we observed no benefit on late outcome. Improved tumor regression does not necessarily lead to a relevant clinical benefit when the neoadjuvant treatment is followed by high-quality surgery.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Graph Sampling for Visual Analytics

Effectively visualizing large graphs and capturing the statistical properties are two challenging tasks. To aid in these two tasks, many sampling approaches for graph simplification have been proposed, falling into three categories: node sampling, edge sampling, and traversal-based sampling. It is still unknown which approach is the best. We evaluate commonly used graph sampling methods through a combined visual and statistical comparison of graphs sampled at various rates. We conduct our evaluation on three graph models: random graphs, small-world graphs, and scale-free graphs. Initial results indicate that the effectiveness of a sampling method is dependent on the graph model, the size of the graph, and the desired statistical property. This benchmark study can be used as a guideline in choosing the appropriate method for a particular graph sampling task, and the results presented can be incorporated into graph visualization and analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Discriminant forest classification method and system

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Secure true random number generation using 1.5-T transistor flash memory

This disclosure relates generally to physically unclonable function (PUF) circuitry along with methods of generating numbers. In one embodiment, the PUF circuitry includes a memory, a memory control circuitry, and whitening circuitry. To reduce or eliminate the systematic bias from the array, whitening circuitry is configured to generate a random number comprising random number bits in response to the memory control circuit implementing at least one sequence of memory cycles on the array of the memory cells in the memory. The whitening circuitry is configured to provide the random number bits of the random number based on the variable bit states stored by the array of the memory cells. On average the whitening circuitry is configured to provide approximately half of the random number bits in the first bit state and half of random number bits in a second bit state.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

A GATE evaluation of the sources of error in quantitative {sup 90}Y PET

Purpose: Accurate reconstruction of the dose delivered by {sup 90}Y microspheres using a postembolization PET scan would permit the establishment of more accurate dose–response relationships for treatment of hepatocellular carcinoma with {sup 90}Y. However, the quality of the PET data obtained is compromised by several factors, including poor count statistics and a very high random fraction. This work uses Monte Carlo simulations to investigate what impact factors other than low count statistics have on the quantification of {sup 90}Y PET. Methods: PET acquisitions of two phantoms—a NEMA PET phantom and the NEMA IEC PET body phantom-containing either {sup 90}Y or {sup 18}F were simulated using GATE. Simulated projections were created with subsets of the simulation data allowing the contributions of random, scatter, and LSO background to be independently evaluated. The simulated projections were reconstructed using the commercial software for the simulated scanner, and the quantitative accuracy of the reconstruction and the contrast recovery of the reconstructed images were evaluated. Results: The quantitative accuracy of the {sup 90}Y reconstructions were not strongly influenced by the high random fraction present in the projection data, and the activity concentration was recovered to within 5% of the known value. The contrast recovery measured for simulated {sup 90}Y data was slightly poorer than that for simulated {sup 18}F data with similar count statistics. However, the degradation was not strongly linked to any particular factor. Using a more restricted energy range to reduce the random fraction in the projections had no significant effect. Conclusions: Simulations of {sup 90}Y PET confirm that quantitative {sup 90}Y is achievable with the same approach as that used for {sup 18}F, and that there is likely very little margin for improvement by attempting to model aspects unique to {sup 90}Y, such as the much higher random fraction or the presence of bremsstrahlung in the singles data.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Detecting hidden transient events in noisy nonlinear time-series

The information impulse function (IIF), running Variance, and local Hölder Exponent are three conceptually different time-series evaluation techniques. These techniques examine time-series for local changes in information content, statistical variation, and point-wise smoothness, respectively. Using simulated data emulating a randomly excited nonlinear dynamical system, this study interrogates the utility of each method to correctly differentiate a transient event from the background while simultaneously locating it in time. Computational experiments are designed and conducted to evaluate the efficacy of each technique by varying pulse size, time location, and noise level in time-series. Our findings reveal that, in most cases, the first instance of a transient event is more easily observed with the information-based approach of IIF than with the Variance and local Hölder Exponent methods. While our study highlights the unique strengths of each technique, the results suggest that very robust and reliable event detection for nonlinear systems producing noisy time-series data can be obtained by incorporating the IIF into the analysis.

42 ENGINEERING↗
DOE OSTI2012

X-ray phase imaging with a paper analyzer

We present a simple x-ray phase imaging method that utilizes the sample-induced distortion of a high contrast random intensity pattern to quantitatively retrieve the two-dimensional phase map at the exit surface of a coherently illuminated sample. This reference pattern is created by placing a sheet of sandpaper in the x-ray beam, with the sample-induced distortion observed after propagation to the detector, a meter downstream. Correlation analysis comparing a single ''sample and sandpaper'' image to a reference ''sandpaper only'' image produces two sensitive differential phase contrast images, giving the sample phase gradient in vertical and horizontal directions. These images are then integrated to recover the projected phase depth of the sample. The simple experimental set-up, retention of flux, and the need for only a single sample image per reconstruction suggest that this method is of value in imaging a range of dynamic processes at both synchrotron and laboratory x-ray sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

A sub-sampled approach to extremely low-dose STEM

The inpainting of deliberately and randomly sub-sampled images offers a potential means to image specimens at a high resolution and under extremely low-dose conditions (≤1 e - /Å 2 ) using a scanning transmission electron microscope. We show that deliberate sub-sampling acquires images at least an order of magnitude faster than conventional low-dose methods for an equivalent electron dose. More importantly, when adaptive sub-sampling is implemented to acquire the images, there is a significant increase in the resolution and sensitivity which accompanies the increase in imaging speed. Lastly, we demonstrate the potential of this method for beam sensitive materials and in-situ observations by experimentally imaging the node distribution in a metal-organic framework.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

Evolution of linear perturbations in Lemaítre-Tolman-Bondi void models

We study the evolution of linear perturbations in a Lemaítre-Tolman-Bondi (LTB) void model with realistic cosmological initial conditions. Linear perturbation theory in LTB models is substantially more complicated than in standard Friedmann universes as the inhomogeneous background causes gauge-invariant perturbations couple at first order. As shown by Clarkson et al. (2009) [1], the evolution is constrained by a system of linear partial differential equations which need to be integrated numerically. We present a new numerical scheme using finite element methods to solve this equation system and generate scalar initial conditions based on Gaussian random fields with an underlying power spectrum for the Bardeen potential. After spherical harmonic decomposition, the initial fluctuations are propagated in time and estimates of angular power spectra of each gauge invariant variable are computed as functions of redshift. This allows to analyse the coupling strength in a statistical way. We find significant couplings up to 25% for large and deep voids of Gpc scale as required to fit the distance redshift relations of SNe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Determining velocity of detonation using high-resolution time domain reflectometry

Two methods are presented to make measurements of the length of a coaxial cable with submillimeter and submicrosecond accuracy. If the cable is destroyed by the passage of a strong shock, for instance, from the detonation of an explosive, a measure of the phase velocity of the detonation (VOD) can be obtained with high accuracy (≈0.25%). The first method introduces a series of short Gaussian electrical pulses (<300 ps) into the cable that reflect off the cable end and are compared to the time of the original outgoing pulse by using a fast digitizer (100 gigasamples per second). By curve fitting a Gaussian form to the outgoing and reflected pulses, a measurement of the cable length can be made with subsample accuracy. So, as long as the pulses do not overlap, a large number may be present in the cable at any time allowing pulse repetition rates of 40–135 MHz depending on the cable length. Averaging allows accurate VOD measurements to be made that are comparable with the best traditional techniques. The second method replaces the pulser with a wide-spectrum (0.1–10 GHz) amplified random noise source. A similar setup and digitizer are used before autocorrelating short (80–160 ns) subsamples of the total waveform to measure the reflected delay time. That is, a smaller amplitude version of the original waveform appears time shifted by twice the transit time in the cable and this time is estimated via autocorrelation. The advantage of this method is that a new subsample needs only to be selected from a time increment in which new spectral information is present for a new measure of the length to be made. In this manner, many more length estimates can be averaged to establish the VOD than with the Gaussian approach. As a result, a detailed description of the implementation of both methods is presented together with an example of the type of data collected and limitations found.

47 OTHER INSTRUMENTATION↗
DOE OSTI2015

Theoretical study of the interparticle interaction of nanoparticles randomly dispersed on a substrate

Metal nanoparticles exhibit the phenomenon of localized surface plasmon resonance (LSPR) due to the collective oscillation of their conduction electrons, which is induced by external electromagnetic radiation. The finite-differential time-domain (FDTD) method is widely used as an electromagnetic field analysis tool for nanoparticles. Although the influence of interparticle interactions is taken into consideration in the FDTD calculation for the plural particles configuration, the FDTD calculation of a random configuration is very difficult, particularly in the case of non-spherical particles. In this study, a theoretical calculation method incorporating interparticle interactions on a substrate with various particle shapes and sizes on a subwavelength scale is developed. The interparticle interaction is incorporated following FDTD calculation with an isolated single particle. This is explained systematically using a signal flow graph. Moreover, the mirror image effect of the substrate and the retardation effect are also taken into account in this method. The validity of this method is verified by calculations for simple arrangements of nanoparticles. In addition, it is confirmed that the method can improve the accuracy of predicted experimental results for Au nanoparticles prepared by the sputtering method, in terms of the plasmon peak wavelength. This method may enable the design of LSPR devices by controlling nanoparticle characteristics, such as the size, shape, and distribution density.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

PARTICLE ACCELERATION IN SUPERLUMINAL STRONG WAVES

We calculate the electron acceleration in random superluminal strong waves (SLSWs) and radiation from them using numerical methods in the context of the termination shocks of pulsar wind nebulae. We pursue the orbit of electrons by solving the equation of motion in the analytically expressed electromagnetic turbulences. These consist of a primary SLS and isotropically distributed secondary electromagnetic waves. Under the dominance of the secondary waves, all electrons gain nearly equal energy. On the other hand, when the primary wave is dominant, selective acceleration occurs. The phase of the primary wave for electrons moving nearly along the wavevector changes very slowly compared with the oscillation of the wave, which is “phase-locked,” and such electrons are continuously accelerated. This acceleration by SLSWs may play a crucial role in pre-shock acceleration. In general, the radiation from the phase-locked population is different from the synchro-Compton radiation. However, when the amplitude of the secondary waves is not extremely weaker than that of the primary wave, the typical frequency can be estimated from synchro-Compton theory using the secondary waves. The primary wave does not contribute to the radiation because the SLSW accelerates electrons almost linearly. This radiation can be observed as a radio knot at the upstream of the termination shocks of the pulsar wind nebulae without counterparts in higher frequency ranges.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Pathologic Response, When Increased by Longer Interval, Is a Marker but Not the Cause of Good Prognosis in Rectal Cancer: 17-year Follow-up of the Lyon R90-01 Randomized Trial

Purpose: The Lyon R90-01 randomized trial investigated whether the interval between preoperative radiation therapy and surgery influenced rectal cancer outcome. Long-term results are reported here after a median follow-up of 17 years. Methods and Materials: Between February 1991 and December 1995, 210 patients from 29 French centers were randomly assigned (ratio of 1:1) to groups that waited either 2 weeks (short interval [SI]) or 6 to 8 weeks (long interval [LI]) between neoadjuvant radiation therapy and surgery. The primary endpoint was sphincter-preserving surgery. Results: LI group showed a better pathologic response (complete response or few residual cells) after radiation therapy than the SI group (26% vs 10.3%, P=.015). A better pathologic response was associated in multivariate analysis with significant improvement of overall survival (pT: P=.0293 and pN: P=.0048) but it was irrespective of the interval duration. The median follow-up was 17.2 years. The 5-, 10-, 15-, and 17-year overall survival rates were, respectively, 66.8%, 48.7%, 40.0%, and 34.0% for the SI group and, respectively, 67.1%, 53.5%, 41.9%, and 34.0% for the LI group. There were no significant differences between groups in terms of survival (P=.7656) or local recurrence rates (SI: 14.4% vs LI: 12.1%, respectively; P=.6202). Of 24 local disease recurrences, 20 (83%) occurred during the first 2 postoperative years, and all but one (96%) occurred during the first 5 postoperative years. The rate of second new malignancies was 9.4% (19 patients). Conclusions: The radiation-induced sterilization rate of the preoperative cancer specimen was a marker of good prognosis. The interval duration (the treatment being the same) although it is modifying the sterilization rate has no impact on survival. Radiation therapy did not postpone local recurrence, because the rate of local relapse after 5 years was low. Radiation-induced cancers after radiation therapy were unusual and should not influence treatment decisions in adults.

62 RADIOLOGY AND NUCLEAR MEDICINE↗