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At least 505 records · Page 28

Assessing the system value of optimal load shifting

We analyze a competitive electricity market, where consumers exhibit optimal load shifting behavior to maximize utility and producers/suppliers maximize their profit under supply capacity constraints. The associated computationally tractable formulation can be used to inform market design or policy analysis in the context of increasing availability of the smart grid technologies that enable optimal load shifting. Through analytic and numeric assessment of the model, we assess the equilibrium value of optimal electricity load shifting, including how the value changes as more electricity consumers adopt associated technologies. For our illustrative numerical case, derived from the Current Trends scenario of the ERCOT Long Term System Assessment, the average energy arbitrage value per ERCOT customer of optimal load shifting technologies is estimated to be $3 for the 2031 scenario year. We assess the sensitivity of this result to the flexibility of load, along with its relationship to the deployment of renewables. Finally, the model presented can also be a starting point for designing system operation infrastructure that communicates with the devices that schedule loads in response to price signals.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Additional Capacity Value From Synergy of Variable Renewable Energy and Energy Storage

Current capacity markets often consider capacity credits from each resource independently, irrespective of the portfolio of resources, potentially overvaluing or undervaluing the capacity contribution of variable renewable energy (VRE) and energy storage (ES) in the grid. We propose a method for calculating the standalone and integrated capacity value of an added VRE resource with existing ES resources. The difference between the integrated and standalone value is the portfolio effect. This is the additional capacity value gained by the synergy of VRE and the existing fleet. Using chronological dispatch simulations and two different reliability metrics to estimate firm capacity, we demonstrate on a small test system that the portfolio effect can be substantial.

capacity credit↗

Reference dosimetry at the Australian Synchrotron's imaging and medical beamline using free-air ionization chamber measurements and theoretical predictions of air kerma rate and half value layer

Purpose: Novel, preclinical radiotherapy modalities are being developed at synchrotrons around the world, most notably stereotactic synchrotron radiation therapy and microbeam radiotherapy at the European Synchrotron Radiation Facility in Grenoble, France. The imaging and medical beamline (IMBL) at the Australian Synchrotron has recently become available for preclinical radiotherapy and imaging research with clinical trials, a distinct possibility in the coming years. The aim of this present study was to accurately characterize the synchrotron-generated x-ray beam for the purposes of air kerma-based absolute dosimetry. Methods: The authors used a theoretical model of the energy spectrum from the wiggler source and validated this model by comparing the transmission through copper absorbers (0.1-3.0 mm) against real measurements conducted at the beamline. The authors used a low energy free air ionization chamber (LEFAC) from the Australian Radiation Protection and Nuclear Safety Agency and a commercially available free air chamber (ADC-105) for the measurements. The dimensions of these two chambers are different from one another requiring careful consideration of correction factors. Results: Measured and calculated half value layer (HVL) and air kerma rates differed by less than 3% for the LEFAC when the ion chamber readings were corrected for electron energy loss and ion recombination. The agreement between measured and predicted air kerma rates was less satisfactory for the ADC-105 chamber, however. The LEFAC and ADC measurements produced a first half value layer of 0.405 {+-} 0.015 and 0.412 {+-} 0.016 mm Cu, respectively, compared to the theoretical prediction of 0.427 {+-} 0.012 mm Cu. The theoretical model based upon a spectrum calculator derived a mean beam energy of 61.4 keV with a first half value layer of approximately 30 mm in water. Conclusions: The authors showed in this study their ability to verify the predicted air kerma rate and x-ray attenuation curve on the IMBL using a simple experimental method, namely, HVL measurements. The HVL measurements strongly supports the x-ray beam spectrum, which in turn has a profound effect on x-ray dosimetry.

61 RADIATION PROTECTION AND DOSIMETRY↗

WE-E-17A-05: Complementary Prognostic Value of CT and 18F-FDG PET Non-Small Cell Lung Cancer Tumor Heterogeneity Features Quantified Through Texture Analysis

Purpose: Previous studies have shown that CT or 18F-FDG PET intratumor heterogeneity features computed using texture analysis may have prognostic value in Non-Small Cell Lung Cancer (NSCLC), but have been mostly investigated separately. The purpose of this study was to evaluate the potential added value with respect to prognosis regarding the combination of non-enhanced CT and 18F-FDG PET heterogeneity textural features on primary NSCLC tumors. Methods: One hundred patients with non-metastatic NSCLC (stage I–III), treated with surgery and/or (chemo)radiotherapy, that underwent staging 18F-FDG PET/CT images, were retrospectively included. Morphological tumor volumes were semi-automatically delineated on non-enhanced CT using 3D SlicerTM. Metabolically active tumor volumes (MATV) were automatically delineated on PET using the Fuzzy Locally Adaptive Bayesian (FLAB) method. Intratumoral tissue density and FDG uptake heterogeneities were quantified using texture parameters calculated from co-occurrence, difference, and run-length matrices. In addition to these textural features, first order histogram-derived metrics were computed on the whole morphological CT tumor volume, as well as on sub-volumes corresponding to fine, medium or coarse textures determined through various levels of LoG-filtering. Association with survival regarding all extracted features was assessed using Cox regression for both univariate and multivariate analysis. Results: Several PET and CT heterogeneity features were prognostic factors of overall survival in the univariate analysis. CT histogram-derived kurtosis and uniformity, as well as Low Grey-level High Run Emphasis (LGHRE), and PET local entropy were independent prognostic factors. Combined with stage and MATV, they led to a powerful prognostic model (p<0.0001), with median survival of 49 vs. 12.6 months and a hazard ratio of 3.5. Conclusion: Intratumoral heterogeneity quantified through textural features extracted from both CT and FDG PET images have complementary and independent prognostic value in NSCLC.

60 APPLIED LIFE SCIENCES↗

SU-E-T-56: A Novel Approach to Computing Expected Value and Variance of Point Dose From Non-Gated Radiotherapy Delivery

Purpose: Randomness in patient internal organ motion phase at the beginning of non-gated radiotherapy delivery may introduce uncertainty to dose received by the patient. Concerns of this dose deviation from the planned one has motivated many researchers to study this phenomenon although unified theoretical framework for computing it is still missing. This study was conducted to develop such framework for analyzing the effect. Methods: Two reasonable assumptions were made: a) patient internal organ motion is stationary and periodic; b) no special arrangement is made to start a non -gated radiotherapy delivery at any specific phase of patient internal organ motion. A statistical ensemble was formed consisting of patient’s non-gated radiotherapy deliveries at all equally possible initial organ motion phases. To characterize the patient received dose, statistical ensemble average method is employed to derive formulae for two variables: expected value and variance of dose received by a patient internal point from a non-gated radiotherapy delivery. Fourier Series was utilized to facilitate our analysis. Results: According to our formulae, the two variables can be computed from non-gated radiotherapy generated dose rate time sequences at the point’s corresponding locations on fixed phase 3D CT images sampled evenly in time over one patient internal organ motion period. The expected value of point dose is simply the average of the doses to the point’s corresponding locations on the fixed phase CT images. The variance can be determined by time integration in terms of Fourier Series coefficients of the dose rate time sequences on the same fixed phase 3D CT images. Conclusion: Given a non-gated radiotherapy delivery plan and patient’s 4D CT study, our novel approach can predict the expected value and variance of patient radiation dose. We expect it to play a significant role in determining both quality and robustness of patient non-gated radiotherapy plan.

60 APPLIED LIFE SCIENCES↗

The value of nodal information in predicting lung cancer relapse using 4DPET/4DCT

Purpose: There is evidence that computed tomography (CT) and positron emission tomography (PET) imaging metrics are prognostic and predictive in nonsmall cell lung cancer (NSCLC) treatment outcomes. However, few studies have explored the use of standardized uptake value (SUV)-based image features of nodal regions as predictive features. The authors investigated and compared the use of tumor and node image features extracted from the radiotherapy target volumes to predict relapse in a cohort of NSCLC patients undergoing chemoradiation treatment. Methods: A prospective cohort of 25 patients with locally advanced NSCLC underwent 4DPET/4DCT imaging for radiation planning. Thirty-seven image features were derived from the CT-defined volumes and SUVs of the PET image from both the tumor and nodal target regions. The machine learning methods of logistic regression and repeated stratified five-fold cross-validation (CV) were used to predict local and overall relapses in 2 yr. The authors used well-known feature selection methods (Spearman’s rank correlation, recursive feature elimination) within each fold of CV. Classifiers were ranked on their Matthew’s correlation coefficient (MCC) after CV. Area under the curve, sensitivity, and specificity values are also presented. Results: For predicting local relapse, the best classifier found had a mean MCC of 0.07 and was composed of eight tumor features. For predicting overall relapse, the best classifier found had a mean MCC of 0.29 and was composed of a single feature: the volume greater than 0.5 times the maximum SUV (N). Conclusions: The best classifier for predicting local relapse had only tumor features. In contrast, the best classifier for predicting overall relapse included a node feature. Overall, the methods showed that nodes add value in predicting overall relapse but not local relapse.

60 APPLIED LIFE SCIENCES↗

SU-F-R-45: The Prognostic Value of Radiotherapy Based On the Changes of Texture Features Between Pre-Treatment and Post-Treatment FDG PET Image for NSCLC Patients

Purpose: The purpose of this research is investigating which texture features extracted from FDG-PET images by gray-level co-occurrence matrix(GLCM) have a higher prognostic value than the other texture features. Methods: 21 non-small cell lung cancer(NSCLC) patients were approved in the study. Patients underwent 18F-FDG PET/CT scans with both pre-treatment and post-treatment. Firstly, the tumors were extracted by our house developed software. Secondly, the clinical features including the maximum SUV and tumor volume were extracted by MIM vista software, and texture features including angular second moment, contrast, inverse different moment, entropy and correlation were extracted using MATLAB.The differences can be calculated by using post-treatment features to subtract pre-treatment features. Finally, the SPSS software was used to get the Pearson correlation coefficients and Spearman rank correlation coefficients between the change ratios of texture features and change ratios of clinical features. Results: The Pearson and Spearman rank correlation coefficient between contrast and SUV maximum is 0.785 and 0.709. The P and S value between inverse difference moment and tumor volume is 0.953 and 0.942. Conclusion: This preliminary study showed that the relationships between different texture features and the same clinical feature are different. Finding the prognostic value of contrast and inverse difference moment were higher than the other three textures extracted by GLCM.

60 APPLIED LIFE SCIENCES↗

Instability of a triangular Abrikosov lattice at values of the Ginzburg–Landau parameter κ close to unity

The “soft” transverse mode of gapless excitations related to the deformation of a triangular Abrikosov lattice with a single flux quantum per unit cell at an arbitrary value of the Ginzburg–Landau parameter κ is investigated. An Abrikosov lattice with the angle φ = π/3 between the unit cell vectors is shown to be unstable in a narrow range of values, 1 < κ < 1.000634. The excitation spectrum of the mode under consideration at low values of the momentum k (in the k{sup 2} approximation) is isotropic at k lying in a plane perpendicular to the magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

RAIS Paducah Background Values

The Paducah Background Values (https://rais.ornl.gov/tools/pgdp_background.html) are from Methods for Conducting Risk Assessments and Risk Evaluations at the Paducah Gaseous Diffusion Plant, Volume 1, Human Health, which sought to establish provisional background values for groundwater and soil. These values were developed by considering agreements reached between the DOE and the regulatory agencies during comment resolution meetings, in the Federal Facility Agreement, and at technical meetings. The Paducah background concentrations are available for soil (surface and subsurface) and groundwater (filtered and unfiltered).

Dolislager, Fred [Oak Ridge National Laboratory (O↗

Which Combinations of Environmental Conditions and Microphysical Parameter Values Produce a Given Orographic Precipitation Distribution?

This study applies an idealized modeling framework, alongside a Bayesian Markov chain Monte Carlo (MCMC) algorithm, to explore which combinations of upstream environmental conditions and cloud microphysical parameter values can produce a particular precipitation distribution over an idealized two-dimensional, bell-shaped mountain. Simulations focus on orographic precipitation produced when an atmospheric river interacts with topography. MCMC-based analysis reveals that different combinations of parameter values produce a similar precipitation distribution, with the most influential parameters being relative humidity (RH), horizontal wind speed (U), surface potential temperature (θ sfc ), and the snow fall speed coefficient (A s ). RH, U, and A s exhibit interdependence: changes in one or more of these factors can be mitigated by compensating changes in the other(s) to produce similar orographic precipitation rates. The results also indicate that the parameter sensitivities and relationships can vary for spatial subregions and given different environmental conditions. In particular, high θ sfc values are more likely to produce the target precipitation rate and spatial distribution, and thus the ensemble of simulations shows a preference for liquid precipitation at the surface. The results presented here highlight the complexity of orographic precipitation controls, and have implications for flood and water management, observational efforts, and climate change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improved Infrared Optical Constants from Pressed Pellets: II. Ellipsometric n and k Values for Ammonium Sulfate with Variability Analysis

Infrared spectral imaging is facilitated via the comparison of spectra recorded in situ to a databank of actual or synthetic infrared reflectance spectra. It has recently been shown that reference spectra corresponding to the many different morphological forms of the same chemical can be generated synthetically using the imaginary, k, and real, n, components of the complex refractive index, n~ = n + ik. One method to obtain the n and k vectors is infrared ellipsometry, which measures the changes in amplitude, tan ?, and phase, ?, of polarized light reflected from the sample both as a function of wavenumber and angle of incidence. The method requires specularly reflected light so best results are usually obtained with polished planar samples of large surface area. Due to the difficulties of obtaining such samples, however, we investigate the possibility of pressing powders of neat materials and obtaining the corresponding optical constants from the pellets. In this paper, variability in the sample pellet and preparation method is investigated, as is variability in the fitting procedure for the derived optical constants. The n/k vectors are derived from the measured ellipsometric parameters, tan ? and ?, as they are fit by an oscillator model which yield n(?) and k(?) vectors as a function of wavenumber, ?. Construction of the oscillator model is not automatic and depends on significant input from the analyst as well as the sample’s physical characteristics. For the pellet pressing, the experimental variability was found to be minimized for size-selected powdered samples as gauged by the minimal variance in ? and ? for three different pellets; similarly, the analytical precision for multiple measurements of the same pellet was also quite good, suggesting that a pressed pellet is a viable sample preparation method. The greatest variability came in the analytic fitting procedure with differences up to 20% arising from four different fits to the same data set. The final ellipsometric n/k data are compared to literature values obtained from crystalline (NH4)2SO4 samples as well as single-angle reflectance measurements that also used pressed pellets. Comparison with the previous literature values shows generally good agreement although higher k-values are observed for the independent sets of data derived from pressed pellets. These data are suggested as an improved set of optical constants for (NH4)2SO4.

optical constants, ellipsometry, ammonium sulfate,↗

Normalization and missing value imputation for label-free LC-MS analysis

Shotgun proteomic data are affected by a variety of known and unknown systematic biases as well as high proportions of missing values. Typically, normalization is performed in an attempt to remove systematic biases from the data before statistical inference, sometimes followed by missing value imputation to obtain a complete matrix of intensities. Here we discuss several approaches to normalization and dealing with missing values, some initially developed for microarray data and some developed specifically for mass spectrometry-based data.

Environmental Molecular Sciences Laboratory↗

Development of Rhodococcus opacus as a chassis for lignin valorization and bioproduction of high-value compounds

The current extraction and use of fossil fuels has been linked to extensive negative health and environmental outcomes. Lignocellulosic biomass-derived biofuels and bioproducts are being actively considered as renewable alternatives to the fuels, chemicals, and materials produced from fossil fuels. A major challenge limiting large-scale, economic deployment of second-generation biorefineries is the insufficient product yield, diversity, and value that current conversion technologies can extract from lignocellulose, in particular from the underutilized lignin fraction. Rhodococcus opacus PD630 is an oleaginous gram-positive bacterium with innate catabolic pathways and tolerance mechanisms for the inhibitory aromatic compounds found in depolymerized lignin, as well as native or engineered pathways for hexose and pentose sugars found in the carbohydrate fractions of biomass. As a result, R. opacus holds potential as a biological chassis for the conversion of lignocellulosic biomass into biodiesel precursors and other value-added products. This review begins by examining the important role that lignin utilization will play in the future of biorefineries and by providing a concise survey of the current lignin conversion technologies. The genetic machinery and capabilities of R. opacus that allow the bacterium to tolerate and metabolize aromatic compounds and depolymerized lignin are also discussed, along with a synopsis of the genetic toolbox and synthetic biology methods now available for engineering this organism. Finally, we summarize the different feedstocks that R. opacus has been demonstrated to consume, and the high-value products that it has been shown to produce. Engineered R. opacus will enable lignin valorization over the coming years, leading to cost-effective conversion of lignocellulose into fuels, chemicals, and materials.

09 BIOMASS FUELS↗

Significance of Metabolic Tumor Volume at Baseline and Reduction of Mean Standardized Uptake Value in {sup 18}F-FDG-PET/CT Imaging for Predicting Pathological Complete Response in Breast Cancers Treated with Preoperative Chemotherapy

Background: The usefulness of {sup 18}F-fluorodeoxyglucose-positron emission tomography/computed tomography for evaluating the treatment efficacy of breast cancers is well-established; however, the predictive values of parameters such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) remain unknown. Methods: This study examined 199 breast cancers treated with primary systemic chemotherapy (PSC) followed by operation, and determined the values of maximum standardized uptake value (SUV{sub max}), peak SUV (SUV{sub peak}), mean SUV (SUV{sub mean}), MTV, and TLG at baseline. Among these cases, data on early changes in these metabolic parameters in 70 breast cancers were also assessed. Results: A pathological complete response (pCR) was achieved in 64 breast cancers. Breast cancers with low MTV at baseline had a significantly higher pCR rate than breast cancers with high MTV (47.9% vs. 23.4%; p = 0.0005). High reduction rates (∆) of SUV{sub max} (p = 0.0001), SUV{sub peak} (p = 0.0001), and SUV{sub mean} (p < 0.0001) resulted in an increased pCR compared with those for low ∆. The pCR rate was highest for the combination of low MTV and high ∆SUV{sub mean} (86.7%), and lowest for high MTV and low ∆SUV{sub mean} (15.4%); the remaining combinations were intermediate (58.6%; p < 0.0001). The combination of low MTV at baseline and high ∆SUV{sub mean} was a significant and independent predictor for pCR (odds ratio 28.63; 95% confidence interval 1.94–422.42; p = 0.0146) in multivariable analysis. Conclusions: Low levels of MTV at baseline and a high reduction of SUV{sub mean} after PSC was significantly associated with pCR. These findings suggest the usefulness of these metabolic parameters for predicting the treatment efficacy of breast cancers.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Retrieval of the complex-valued refractive index of germanium near the M 4,5 absorption edge

The complex-valued index of refraction of germanium in the extreme ultraviolet (XUV) is measured by multiangle reflectance of synchrotron radiation. The resulting index of refraction is higher resolution than previously measured values. It reveals new structures attributed to transitions from the 3d-core orbitals to the $Σ^{c}_{5,2}$ and the $X^{c}_{5,2}$ conduction bands. Additionally, it is shown that the problem of total external reflection, which renders multi-angle reflectance measurements insensitive to the complex-valued refractive index at grazing incidence, can be overcome by employing measurements at angles of incidence away from the critical angle.

36 MATERIALS SCIENCE↗

Value-of-Information Analysis of a Fracture Prediction Method

A core-based fracture prediction method is used to illustrate a Value of Information (VOI) decision-analysis protocol to inform completion decisions in tight-gas sandstones. The ratio of late host-rock cement to available pore volume or degradation index uses petrographic observations of cement distributions in core (including sidewall cores) to predict whether nearby but unsampled fractures (widths > 0.5 to 1 mm) are sealed (non-conductive) or open (conductive). Measurements from four sandstone plays suggest that the index correctly predicts open vs. sealed fractures with an accuracy in excess of 80%. The value added is calculated using Bayesian inference in which accuracy of the index serves as the likelihood of the prior distribution of open fractures to assess the posterior probability that data represent a useful predictor of producibility. VOI of the prediction method is more than three times the cost to acquire the data. VOI is most sensitive to play-specific geologic and cost parameters including cost to drill, expected revenue from a successful well, cost of completion, cost of acquiring data for the index, and fracture probability distributions. The approach provides a way to value acquiring fracture data and points to a need for zone-specific production data in tight-gas sandstones.

02 PETROLEUM↗

High-Performance Buildings – Value, Messaging, Financial and Policy Mechanisms

At the request of the Pacific Northwest National Laboratory, an in-depth analysis of the rapidly evolving state of real estate investments, high-performance building technology, and interest in efficiency was conducted by HaydenTanner, LLC, for the U.S. Department of Energy (DOE) Building Technologies Program. The analysis objectives were • to evaluate the link between high-performance buildings and their market value • to identify core messaging to motivate owners, investors, financiers, and others in the real estate sector to appropriately value and deploy high-performance strategies and technologies across new and existing buildings • to summarize financial mechanisms that facilitate increased investment in these buildings. To meet these objectives, work consisted of a literature review of relevant writings, examination of existing and emergent financial and policy mechanisms, interviews with industry stakeholders, and an evaluation of the value implications through financial modeling. This report documents the analysis methodology and findings, conclusion and recommendations. Its intent is to support and inform the DOE Building Technologies Program on policy and program planning for the financing of high-performance new buildings and building retrofit projects.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Overcoming the Recalcitrance of Cellulosic Biomass by Value Prior to Pulping (CRADA Final Report)

The Value Prior to Pulping (VPP) project goal was to demonstrate the technical and commercial feasibility of introducing a new value stream into existing pulp and paper mills. Essentially the intent was to transfer the energy content of extracted hemicellulose from electricity and steam generated in the recovery boiler to a liquid transportation fuel. The hemicellulose fraction was extractedprior to pulping, fractionated, or conditioned if necessary, and fermented to ethanol. Commercial adaptation of the process to wood hemicelluloses was a prerequisite for using this less currently valued component available from biomass and wood. These hemicelluloses are predominately glucurono-xylan in hardwoods and galactoglucomannan in softwoods (with a significant softwood component of anarabino-xylan) and will yield fermentation substrates different from cellulose. NREL provided its expertise in the area of fermentation host evaluation using its Zymomonas strains on the CleanTech Partner's (CTP) VPP project. The project was focused on the production of fuel ethanol and acetic acid from hemicellulose streams generated from wood chips of industrially important hardwood andsoftwood species. NREL was one of four partners whose ethanologen was tested on the hydrolyzed extracts. The use of commercially available enzymes to treat oligomeric sugar extracts was also investigated and coupled with fermentation. Fermentations by NREL were conducted with the Zymomonas mobilis organism with most of the work being performed with the 8b strain. The wood extracts hydrolyzedand/or fermented by NREL were those derived from maple, mixed southern hardwoods, and loblolly pine. An unhydrolyzed variant of the mixed southern hardwood extract possessed a large concentration of oligomeric sugars and enzymatic hydrolysis was performed with a number of enzymes, followed by fermentation. The fermentation of the wood extracts was carried out at bench scale in flasks or smallbioreactors, with a maximum volume of 500 mL.

09 BIOMASS FUELS↗