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DOE OSTI2022

Benefit Analysis of CO 2 Delivery Options for Offshore Storage or Enhanced Oil Recovery

The analysis presented in this report evaluates the benefits of CO₂ offshore transport via pipeline or ship within the GOM. It takes a top-down framework to estimate the costs. First, this analysis designed a reduced-order model (ROM) based on the cash flows in the FECM/NETL CO₂ Transport Cost Model (also known as CO2_T_COM). The ROM takes capital expenses (CAPEX) and operating expenses (OPEX) to calculate the CO₂ breakeven price based on the cash flows. Second, this analysis developed regression models utilizing published data from other analyses to estimate CAPEX and OPEX. Since the ROM is a simplified cash flow calculation, it is easy to exchange the core regression models to estimate various costs. The ROM and regression models provided a framework that can be easily used by other researchers, decision-makers, operators, and regulators. The objective of this analysis is to assess the CO₂ breakeven cost range for pipeline and ship transport of captured CO₂ given the CO₂ source and storage reservoir located in the GOM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS1987

Fault-tolerant clock synchronization validation methodology

A validation method for the synchronization subsystem of a fault-tolerant computer system is presented. The high reliability requirement of flight-crucial systems precludes the use of most traditional validation methods. The method presented utilizes formal design proof to uncover design and coding errors and experimentation to validate the assumptions of the design proof. The experimental method is described and illustrated by validating the clock synchronization system of the Software Implemented Fault Tolerance computer. The design proof of the algorithm includes a theorem that defines the maximum skew between any two nonfaulty clocks in the system in terms of specific system parameters. Most of these parameters are deterministic. One crucial parameter is the upper bound on the clock read error, which is stochastic. The probability that this upper bound is exceeded is calculated from data obtained by the measurement of system parameters. This probability is then included in a detailed reliability analysis of the system.

Computer systems↗

DOE OSTI2012

Fuel Cycle Research & Development Technical Monthly – May 2012

Management and Integration LANL - Initial coordination meetings with NE and NA-20 were held the first week of May. Additional meetings, to include NA-82 and the new Proliferation and Terrorism Risk Assessment task are scheduled for June. Work package planning as part of the NTD transition is ongoing. Microcalorimetry LANL - Some parts to attempt repair of a malfunctioning water chiller that has been holding up work on the current detector array have arrived. We will attempt to begin running the compressor/cryostat next week to resume work on commissioning the detector array. We have also been working on a backup plan to temporarily move our system to a different lab space. Completed data analysis and prepared a paper summarizing Pu measurements for peer-review journal. Two members of our team presented work at the SORMA West 2012 conference. Completed data analysis and prepared a milestone report summarizing the development of Monte Carlo tools to study systematic errors. Electrochemical Sensor INL - The second sensor test was stopped short due to the work stand-down. Some activities related to this work have resumed, but not all. The sensor used during the second test was removed from the furnace and it showed cracks and later crumbled when being rinsed for sample preparation. The sensor material will be submitted to SEM analysis once work is resumed in the facilities where analysis is performed. A third sensor test has started. Tests with different arrangements will continue and will be oriented based on post-test analysis of the first three sensor tests. Materials with different annealing temperatures will also be prepared for analysis. Lead slowing down spectrometer LANL - Continued work on perturbation method for LSDS analysis. We are running simulations to delineate issues and are checking additional data libraries to see whether there are differences in simulation results. Electrochemical sensor INL - The second sensor test was stopped short due to the work stand-down. Some activities related to this work have resumed, but not all. The sensor used during the second test was removed from the furnace and it showed cracks and later crumbled when being rinsed for sample preparation. The sensor material will be submitted to SEM analysis once work is resumed in the facilities where analysis is performed. A third sensor test has started. Tests with different arrangements will continue and will be oriented based on post-test analysis of the first three sensor tests. Materials with different annealing temperatures will also be prepared for analysis. Fast Neutron Multiplicity analysis INL - The University of Michigan team continues its work on the post-experiment analysis of the validation data from JRC ISPRA, as well as scoping studies using the simulation tool MCNPX-PoliMi. At INL, our new staff member working on this project is now working to model performance capabilities for the fast-neutrons scintillator design concepts. At INL our primary analysis approach is focused on the Feynman mean-to-variance approach. At the University of Michigan, the primary analysis approach is multiplicity coincidence analysis. Fast Neutron Imaging to Quantify Nuclear Materials ORNL - Completed additional measurements of the two 'trainer' configurations as well as calibration measurements with sources on an x-y stage. The imager was shipped to Pantex for an NA-22 obligation at the end of May. Lead Slowing Down Spectrometer LANL - Continued to look into He4 detector. A Swiss company was located that makes He4 detectors and associated electronics. Had a teleconference with them to assess the possible help we can get from them. We are also looking in to constructing one locally. Ongoing perturbation calculations are providing information on the fundamental systematic error limits of LSDS. In order to achieve separating the contribution of Pu and 235U to the signal, there will need to be tight controls on systematic errors. Multi-isotope Process Monitor PNNL - Attended a training call in advanced multivariate classification and analysis methods. These methods were applied to the multivariate analysis of fuel characteristics based on simulated gamma. Work continued on a computational framework to quantify the impact of gamma-ray counting statistical precision on principal component regression (PCR) analysis of a multi-component (i.e. multi-isotope) gammaray spectrum. Tests of the simulation framework are anticipated to begin in early June. Development of a proposal to instrument H-Canyon is being prepared in conjunction with SRNL and the NNSA's NGSI program is ongoing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Quantitative metrics for evaluating thermonuclear design codes and physics models applied to the National Ignition Campaign

In this study, physics models and design codes for hot dense plasmas undergoing thermonuclear burn are evaluated objectively using statistical metrics that compare the difference between calculations and data relative to the experimental uncertainties. The analysis is applied to the National Ignition Campaign (NIC) because it is relevant, comprehensive, and well documented. The statistics confirm that a key process afflicting NIC performance is mix driven by hydrodynamic instabilities as approximated here using the KL model [G. Dimonte and R. Tipton, Phys. Fluids 18, 085101 (2006)]. New physics models are also presented for instability-driven magnetic fields [B. Srinivasan et al., Phys. Rev. Lett. 108, 165002 (2012)] and the Coulomb logarithm for electron–ion thermal relaxation [G. Dimonte and J. Daligault, Phys. Rev. Lett. 101, 135001 (2008)]. The plasma-generated magnetic fields improve the agreement between code and data in a statistically significant manner by reducing the electron thermal conduction in the hot-spot via the Hall term. The Coulomb logarithm is presented in a numerically practical form that incorporates recent theoretical advances. However, it does not improve the agreement between the code and data because the thermal relaxation is so fast in non-ignited NIC plasmas that the typical 20% error does not change the tight coupling between electrons and ions. Even with these improved physics models, the one-dimensional simulations presented here are not able to describe the high-convergence NIC implosions in a statistically acceptable manner. Of the heroic multi-dimensional simulations of Clark et al. [Phys. Plasmas 23, 056302 (2016)], only those in three-dimensions satisfy the statistical acceptance criterion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Timing of treatment in small-cell lung cancer

Small-cell lung cancer (SCLC) is an aggressive disease with poor survival and rapid doubling time. Current practice is to treat SCLC as soon as possible but evidence on appropriate timing of treatment from diagnosis (TTD) is lacking. This is a retrospective analysis of SCLC patients from the 2012 to 2015 Kentucky Cancer Registry. Data collected included age at diagnosis, stage, gender, race, insurance and treatment. Factors and survival associated with TTD were identified with logistic regression analyses and Cox proportional hazards models. Among the 2992 SCLC patients, 2371 (79%) of SCLC patients were treated with one or more treatment modalities. Among treated patients, 93% received chemotherapy ± radiation with the mean TTD of 18 days. Most patients (80%) have TTD of ≤ 4 weeks with 33% treated within 1 week, 20% 1–2 weeks, and 27% 2–4 weeks from diagnosis. Delay in treatment (TTD > 4 weeks) was less in stage III and IV disease (odds ratio: 0.33 and 0.27 respectively, p < 0.01) but not significantly associated with age, race, gender, and insurance. One and two-year survival of patients with TTD ≤ 4 weeks was significantly worse when compared to > 4 weeks (hazard ratio = 1.43, 95% CI 1.2–1.6, p < 0.01; HR = 1.45, 95% CI 1.3–1.6, p < 0.01 respectively). These results show a trend toward better survival with late treatment of SCLC. Therefore, a general urgency to treat SCLC needs to be re-evaluated with consideration of patients needing more optimization before treatment. Further studies are needed to better clarify the appropriate timing of treatment from diagnosis in SCLC and who will benefit from early versus late treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2011

Dose Escalation and Quality of Life in Patients With Localized Prostate Cancer Treated With Radiotherapy: Long-Term Results of the Dutch Randomized Dose-Escalation Trial (CKTO 96-10 Trial)

Purpose: To assess the impact of dose escalation of radiotherapy on quality of life (QoL) in prostate cancer patients. Patients and Methods: Three hundred prostate cancer patients participating in the Dutch randomized trial (CKTO 69-10) comparing 68 Gy with 78 Gy were the subject of this analysis. These patients filled out the SF-36 QoL questionnaire before radiotherapy (baseline) and 6, 12, 24, and 36 months thereafter. Changes in QoL over time of {>=}10 points were considered clinically relevant. Repeated-measures regression analyses were applied to estimate and test the QoL changes over time, the differences between the two arms, and for association with a number of covariates. Results: At 3-year follow-up, the summary score physical health was 73.2 for the 68-Gy arm vs. 71.6 for the 78-Gy arm (p = 0.81), and the summary score mental health was 76.7 for the 68-Gy arm vs. 76.1 for the 78-Gy arm (p = 0.97). Statistically significant (p < 0.01) deterioration in QoL scores over time was registered in both arms in six scales. The deterioration over time was more pronounced in the high-dose arm for most scales. However, clinically relevant deterioration (>10 points) was seen for only two scales. None of the tested covariates were significantly correlated with QoL scores. Conclusion: Dose escalation did not result in significant deterioration of QoL in prostate cancer patients. In both randomization arms, statistically significant decreases in QoL scores over time were seen in six scales. The deterioration of QoL was more pronounced in the physical than in the mental health domain and in some scales more in the high- than in the low-dose arm, but the differences between arms were not statistically significant.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Machine learning changes the rules for flux limiters

Learning to integrate non-linear equations from highly resolved direct numerical simulations has seen recent interest for reducing the computational load for fluid simulations. Here, we focus on determining a flux-limiter for shock capturing methods. Focusing on flux limiters provides a specific plug-and-play component for existing numerical methods. Since their introduction, an array of flux limiters has been designed. Using the coarse-grained Burgers' equation, we show that flux-limiters may be rank-ordered in terms of their log-error relative to high-resolution data. We then develop a theory to find an optimal flux-limiter and present flux-limiters that outperform others tested for integrating Burgers' equation on lattices with [Formula: see text], and 2x, 3x, 4x, and 8x coarse-grainings. We train a continuous piecewise linear limiter by minimizing the mean-squared misfit to six-grid point segments of high-resolution data, averaged over all segments. While flux limiters are generally designed to have an output of φ(r) = 1 at a flux ratio of r = 1, our limiters are not bound by this rule and yet produce a smaller error than standard limiters. Here we find that our machine learned limiters have distinctive features that may provide new rules-of-thumb for the development of improved limiters. Additionally, we use our theory to learn flux-limiters that outperform standard limiters across a range of values (as opposed to at a specific fixed value) of coarse-graining, number of discretized bins, and diffusion parameter. This demonstrates the ability to produce flux limiters that should be more broadly useful than standard limiters for general applications.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

Understanding software faults and their role in software reliability modeling

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Munson, John C.↗

DOE OSTI2019

Cardiorespiratory fitness and health‐related quality of life in adolescents: A longitudinal analysis from the LabMed Physical Activity Study

Abstract Objective The purpose of this study was to examine the longitudinal associations between cardiorespiratory fitness and health‐related quality of life (HRQoL) in a sample of adolescents, and to determine whether changes in cardiorespiratory fitness were associated with HRQoL over a 2‐year follow‐up. Methods This is a longitudinal analysis with 571 Portuguese adolescents (274 boys and 297 girls) aged 12‐18 years. HRQoL was measured with the Kidscreen‐10 questionnaire; the 20 m shuttle‐run was used to estimate cardiorespiratory fitness; socioeconomic status was assessed with the Family Affluence Scale; and pubertal stage was assessed with Tanner stages. Linear regression and analysis of covariance ( ancova s) were used to examine the associations between cardiorespiratory fitness and HRQoL. Results HRQoL decreased over a 2‐year period both in boys and girls ( P < .05). Moreover, girls at baseline and at follow‐up reported significantly lower HRQoL values than boys (between subjects P < .001). After adjustments for potential confounders, regression analyses showed significant cross‐sectional associations between cardiorespiratory fitness and HRQoL both at baseline ( B = 0.095; P = .023) and at follow‐up (B = 0.090; P = .012). ancova showed that adolescents whose cardiorespiratory fitness decreased over time exhibited lower scores of HRQoL at follow‐up, compared to those with persistent high cardiorespiratory fitness; this held after adjustments for age, sex, socioeconomic status, and pubertal stage. Conclusions Changes in cardiorespiratory fitness during adolescence were associated with HRQoL over a 2‐year period. This study suggests that improving cardiorespiratory fitness could be an important strategy in improving the HRQoL of adolescents.

Evaristo, Olga S.↗

DOE OSTI2019

Comparison of CT methods for determining graft steatosis in living donor liver transplantation

Purpose: To evaluate and compare the diagnostic performance of non-enhanced computed tomography (NECT) and contrast-enhanced CT (CECT) attenuation indices in the assessment of hepatic steatosis by using biopsy as the reference standard. Materials and methods: This retrospective study was approved by our Institutional Review Board. 55 Potential donors who underwent both NECT and triphasic CECT and core liver biopsy, were included the study. Average attenuation measurements that were obtained from multiple regions in liver, spleen, and psoas muscle on both unenhanced and CECT were used for analysis. Hepatic attenuation measurements were analyzed with and without normalization with the spleen and psoas muscle. Linear regression and receiver operating characteristic (ROC) curve analysis were used to evaluate the statistical association between CT indices and steatosis at histology. Results: Linear regression analysis confirmed the strongest correlation between steatosis and normalized measurements of hepatic attenuation with splenic attenuations on hepatic venous phase of CECT scan (R 0.821; R{sup 2} 0.674 and R 0.816; R{sup 2} 0.665, respectively). The use of ROC curve analysis also demonstrated that normalized measurements of hepatic attenuation with splenic attenuations on hepatic venous phase of CECT showed high diagnostic performance regarding the qualitative distinction of steatosis (AUC values greater than 0.9). Conclusion: Attenuation measurements of liver normalized with spleen on hepatic venous phase may be useful in evaluating steatosis in donor candidates with moderate to severe steatosis who are unacceptable for liver donation. In this manner unnecessary liver biopsy may be avoided in those donor candidates.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

Fenitrothion action at the endocannabinoid system leading to spermatotoxicity in Wistar rats

Organophosphate (OP) compounds as anticholinesterase agents may secondarily act on diverse serine hydrolase targets, revealing unfavorable physiological effects including male reproductive toxicity. The present investigation proposes that fenitrothion (FNT, a major OP compound) acts on the endocannabinoid signaling system in male reproductive organs, thereby leading to spermatotoxicity (sperm deformity, underdevelopment, and reduced motility) in rats. FNT oxon (bioactive metabolite of FNT) preferentially inhibited the fatty acid amide hydrolase (FAAH), an endocannabinoid anandamide (AEA) hydrolase, in the rat cellular membrane preparation from the testis in vitro. Subsequently, male Wistar rats were treated orally with 5 or 10 mg/kg FNT for 9 weeks and the subchronic exposure unambiguously deteriorated sperm motility and morphology. The activity-based protein profiling analysis with a phosphonofluoridate fluorescent probe revealed that FAAH was selectively inhibited among the FNT-treated cellular membrane proteome in testis. Intriguingly, testicular AEA (endogenous substrate of FAAH) levels were elevated along with the FAAH inhibition caused by the subchronic exposure. More importantly, linear regression analyses for the FNT-elicited spermatotoxicity reveal a good correlation between the testicular FAAH activity and morphological indices or sperm motility. Accordingly, the present study proposes that the FNT-elicited spermatotoxicity appears to be related to inhibition of FAAH leading to overstimulation of the endocannabinoid signaling system, which plays crucial roles in spermatogenesis and sperm motility acquirement. - Highlights: • Subchronic exposure to fenitrothion induces spermatotoxicity in rats. • The fatty acid amide hydrolase is a potential target for the spermatotoxicity. • Overstimulation of the endocannabinoid signal possibly leads to the spermatotoxicity.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Deep Learning for Multigroup Cross-Section Representation in Two-Step Core Calculations

Here we investigate using deep learning, a type of machine-learning algorithm employing multiple layers of artificial neurons, for the mathematical representation of multigroup cross sections for use in the Griffin reactor multiphysics code for two-step deterministic neutronics calculations. A three-dimensional fuel element typical of a high-temperature gas reactor as well as a two-dimensional sodium-cooled fast reactor lattice are modeled using the Serpent Monte Carlo code, and multigroup macroscopic cross sections are generated for various state parameters to produce a training data set and a separate validation data set. A fully connected, feedforward neural network is trained using the open-source PyTorch machine-learning framework, and its accuracy is compared against the standard piecewise linear interpolation model. Additionally, we provide in this work a generic technique for propagating the cross-section model errors up to the k eff using sensitivity coefficients with the first-order uncertainty propagation rule. Quantifying the eigenvalue error due to the cross-section regression errors is especially practical for appropriately selecting the mathematical representation of the cross sections. We demonstrate that the artificial neural network model produces lower errors and therefore enables better accuracy relative to the piecewise linear model when the cross sections exhibit nonlinear dependencies; especially when a coarse grid is employed, where the errors can be halved by the artificial neural network. However, for linearly dependent multigroup cross sections as found for the sodium-cooled fast reactor case, a simpler linear regression outperforms deeper networks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

Improved $b$-jet Energy Correction for $H \to b\bar{b}$ Searches at CDF

We present a method for improving the $b$-jet energy resolution in order to improve the signal sensitivity in searches for particles decaying to a $b$ quark and anti-$b$ quark. A correction function is computed for individual jets, which combines information from the secondary vertex tagger, the offline tracking and standard calorimeter-based jet-energy reconstruction algorithm in order to provide a more accurate measurement of the true $b$-quark energy. We apply the correction to Monte-Carlo-simulated jets in the process $WH \rightarrow \ell \nu b\bar b$ and find an improvement in both the mean and the resolution of the $b$-jet energy with respect to the $b$-quark energy. The correction improves the measured Higgs dijet invariant mass resolution from $\sim$ 15%(standard jet corrections) to $\sim$ 11%(improved jet corrections) in the Higgs mass range from 100 GeV/$c^2$ - 150 GeV/$c^2$. Using the corrected $b$-jet energies instead of the standard calorimeter-based $b$-jet energies results in a $\sim$ 9% improvement in the expected sensitivity for Higgs boson production cross section in the most sensitive search region of the $WH \rightarrow \ell \nu b\bar b$ analysis, which is two tagged jets and one charged central lepton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Considerations for AMI-Based Operations for Distribution Feeders

More than $5 billion in investments in advanced metering infrastructure (AMI) technologies, AMI deployments, as pervasive secondary network voltage monitoring systems, provide opportunities for utility operations and controls. This paper focuses on the considerations for AMI-based tools and techniques as the industry moves toward operationalizing such large data sets. Phase identification is a first such tool. Numerous distribution network analysis, monitoring, and control applications - including volt/volt-ampere reactive control, state estimation, and distribution automation - require accurate phase connectivity information in the system models. The phase connectivity database maintained by utilities is inaccurate because of a significant amount of missing data, restoration activities, and network reconfiguration. Existing phase identification techniques that estimate phase connectivity work well in distribution feeders that have low or no photovoltaic (PV) generation; however, they fail to identify the phases accurately when considerable PV generation is present. This work addresses the phase identification problem in the presence of high PV generation using statistical analysis methods. Further, insights into the AMI data requirements for this application in terms of data window length and resolution are provided using sensitivity analysis performed on an actual distribution feeder model of San Diego Gas & Electric Company. The results of this study show that the phase connectivity, even in the presence of high PV generation, can be accurately identified using statistical analysis of AMI data of 1 day.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Considerations for AMI-Based Operations for Distribution Feeders: Preprint

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Surgical Management of the Axilla in Clinically Node-Positive Patients Receiving Neoadjuvant Chemotherapy: A National Cancer Database Analysis

Background: The feasibility of sentinel lymph node biopsy (SLNB) in patients with clinically node-positive (cN+) disease who convert to clinically node-negative (cN0) disease following neoadjuvant chemotherapy (NAC) has been evaluated in several large clinical trials, but it remains unclear whether the approach has been broadly adopted in the United States. Methods: The National Cancer Database was used to identify women diagnosed with cN+ breast cancer who received NAC followed by surgery between 2012 and 2015. Trends in axillary surgery were evaluated and multivariable logistic regression analyses performed to determine factors associated with receipt of SLNB. Results: Of 12,965 women cN+ at baseline, the use of SLNB increased from 31.8% in 2012 to 49% in 2015 (p < 0.001). Using axillary pCR as a surrogate for patients who convert to cN0 following NAC, among 5127 (39.5%) ypN0 patients, SLNB increased from 38.2 to 58.4% over the study period (p < 0.001), resulting in avoidance of axillary dissection in 42.2% of ypN0 patients by 2015. In adjusted analyses, factors significantly associated with SLNB attempt included cN1 disease, age < 45 years, treatment facility type, triple-negative and HER2-positive subtypes, and year of diagnosis. In women with residual isolated tumor cells (ITCs), micrometastases, and ypN1 disease, SLNB was the only axillary procedure performed in 36.9%, 23.6%, and 13.0% of cases. Conclusions: The use of SLNB in cN+ patients receiving NAC increased significantly between 2012 and 2015. SLNB alone was performed in more than 10% of patients with ypN1 disease, 20% with micrometastases, and 35% with ITCs; the oncologic safety of omitting axillary dissection in these patients requires further evaluation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2012

Prediction of Total Dissolved Gas Exchange at Hydropower Dams

Total dissolved gas (TDG) supersaturation in waters released at hydropower dams can cause gas bubble trauma in fisheries resulting in physical injuries and eyeball protrusion that can lead to mortality. Elevated TDG pressures in hydropower releases are generally caused by the entrainment of air in spillway releases and the subsequent exchange of atmospheric gasses into solution during passage through the stilling basin. The network of dams throughout the Columbia River Basin (CRB) are managed for irrigation, hydropower production, flood control, navigation, and fish passage that frequently result in both voluntary and involuntary spillway releases. These dam operations are constrained by state and federal water quality standards for TDG saturation which balance the benefits of spillway operations designed for Endangered Species Act (ESA)-listed fisheries versus the degradation to water quality as defined by TDG saturation. In the 1970s, the United States Environmental Protection Agency (USEPA), under the federal Clean Water Act (Section 303(d)), established a criterion not to exceed the TDG saturation level of 110% in order to protect freshwater and marine aquatic life. The states of Washington and Oregon have adopted special water quality standards for TDG saturation in the tailrace and forebays of hydropower facilities on the Columbia and Snake Rivers where spillway operations support fish passage objectives. The physical processes that affect TDG exchange at hydropower facilities have been studied throughout the CRB in site-specific studies and routine water quality monitoring programs. These data have been used to quantify the relationship between project operations, structural properties, and TDG exchange. These data have also been used to develop predictive models of TDG exchange to support real-time TDG management decisions. These empirically based predictive models have been developed for specific projects and account for both the fate of spillway and powerhouse flows in the tailrace channel and resultant exchange in route to the next downstream dam. Currently, there exists a need to summarize the general finding from operational and structural TDG abatement programs conducted throughout the CRB and for the development of a generalized prediction model that pools data collected at multiple projects with similar structural attributes. A generalized TDG exchange model can be tuned to specific projects and coupled with water regulation models to allow the formulation of optimal daily water regulation schedules subject to water quality constraints for TDG supersaturation. A generalized TDG exchange model can also be applied to other hydropower dams that affect TDG pressures in tailraces and can be used to develop alternative operational and structural measures to minimize TDG generation. It is proposed to develop a methodology for predicting TDG levels downstream of hydropower facilities with similar structural properties as a function of a set of variables that affect TDG exchange; such as tailwater depth, spill discharge and pattern, project head, and entrainment of powerhouse releases. TDG data from hydropower facilities located throughout the northwest region of the United States will be used to identify relationships between TDG exchange and relevant dependent variables. Data analysis and regression techniques will be used to develop predictive TDG exchange expressions for various structural categories.

13 HYDRO ENERGY↗

DOE OSTI2016

Uncertainty analysis of terrestrial net primary productivity and net biome productivity in China during 1901-2005

Here, despite the importance of net primary productivity (NPP) and net biome productivity (NBP), estimates of NPP and NBP for China are highly uncertain. To investigate the main sources of uncertainty, we synthesized model estimates of NPP and NBP for China from published literature and the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). The literature-based results showed that total NPP and NBP in China were 3.35 ± 1.25 and 0.14 ± 0.094 Pg C yr –1 , respectively. Classification and regression tree analysis based on literature data showed that model type was the primary source of the uncertainty, explaining 36% and 64% of the variance in NPP and NBP, respectively. Spatiotemporal scales, land cover conditions, inclusion of the N cycle, and effects of N addition also contributed to the overall uncertainty. Results based on the MsTMIP data suggested that model structures were overwhelmingly important (>90%) for the overall uncertainty compared to simulations with different combinations of time-varying global change factors. The interannual pattern of NPP was similar among diverse studies and increased by 0.012 Pg C yr –1 during 1981–2000. In addition, high uncertainty in China's NPP occurred in areas with high productivity, whereas NBP showed the opposite pattern. Our results suggest that to significantly reduce uncertainty in estimated NPP and NBP, model structures should be substantially tested on the basis of empirical results. To this end, coordinated distributed experiments with multiple global change factors might be a practical approach that can validate specific structures of different models.

54 ENVIRONMENTAL SCIENCES↗