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At least 1,387 records · Page 77

A method for including external feed in depletion calculations with CRAM and implementation into ORIGEN

A method for including external feed with polynomial time dependence in depletion calculations with the Chebyshev Rational Approximation Method (CRAM) is presented and the implementation of CRAM to the ORIGEN module of the SCALE suite is described. In addition to being able to handle time-dependent feed rates, the new solver also adds the capability to perform adjoint calculations. Results obtained with the new CRAM solver and the original depletion solver of ORIGEN are compared to high precision reference calculations, which shows the new solver to be orders of magnitude more accurate. Lastly, in most cases, the new solver is up to several times faster due to not requiring similar substepping as the original one.

97 MATHEMATICS AND COMPUTING↗

Turbine scale and siting considerations in wind plant layout optimization and implications for capacity density

Improvements in wind energy technology, reduced costs, and ambitious clean energy goals have led to projections of high wind contribution in coming years. Developing methodologies to design wind plants with a variety of siting constraints and turbine sizes helps enable high wind penetration, and gain a better understanding of how wind plants are sensitive to setback constraints and turbine design. In this paper, we present a two-step optimization method to simultaneously determine the optimal number of turbines and their locations in a wind plant domain divided into many small, discrete parcels. We present the optimized performance metrics of a wind plant optimized with different turbine sizes and ratings, and with different siting restrictions within the wind plant. Our results indicate that taller and larger turbines are more sensitive to increasing siting constraints. We also compare the optimal wind plant layouts and performance for wind plants optimized for minimum COE and maximum profit. Wind plants optimized for profit had 130%-190% of the capacity of plants optimized for COE, which demonstrates that the optimal results are greatly affected by the objective function, which should be carefully considered. Finally, in this paper we demonstrate the effect of increasing siting constraints on wind plant capacity density, and how the results change when different land areas are used to calculate capacity density. When using the entire wind plant boundary area to determine capacity density, increasing siting constraints decreases the capacity density. However, when we only use the available area (the area left after removing the siting constraints) to calculate the capacity density, increasing the siting constraints increases capacity density. This is a critical insight because of how capacity density is typically defined and used in research, and has important implications for assessment of technical potential and capacity expansion modeling, as well as future wind deployment potential.

17 WIND ENERGY↗

Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Realistic operation of two residential cordwood-fired outdoor hydronic heater appliances—Part 2: Particle number and size

The use of wood as a fuel for home heating is a concern from an environmental health and safety perspective as biomass combustion appliances emit high concentrations of particulate matter. Wood burning significantly contributes to wintertime particulate matter concentrations in many states in the northern United States. Of particular concern are outdoor wood-fired hydronic heaters. These devices are concerning as they tend to have very large combustion chambers and typical use patterns can result in long periods of low output, which result in an increased particulate matter emission rate relative to high heat output operating conditions. In this study, the performance of two hydronic heaters operating under different combustion conditions, including four different heat output categories approximately corresponding to categories I–IV denoted in Environmental Protection Agency Method 28 Outdoor Wood-fired Hydronic Heaters, and during start-up and reloading events were investigated. Measurements of flue gas particulate number concentration and size for particles with aerodynamic diameters between 0.006 and 10 µm were made using a dilution sampling system. The measured particle number concentration in the flue gas was between 0.71 and 420 million particles per cubic centimeter and was dependent on fuel loading and heat output. For each hydronic heater tested, the highest average particle concentration was found at the beginning of each test during the cold-start condition. Additionally, the majority of the particles had aerodynamic diameters less than 0.100 µm (particles of this size made up between 64% and 97% of all particles) and less than 1% of all particles had aerodynamic diameters greater than 1 µm for all phases. For particles in the accumulation mode, between 0.100 and 1 µm, the mean particle diameter was dependent on fuel loading and heat output.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Network Detection of Radiation Sources Using Localization-Based Approaches

Radiation source detection is a critical problem in homeland security-related applications. Deploying a network of detectors is expected to provide improved detection due to the combined, albeit dispersed, capture area of multiple detectors. Recently, localization-based detection algorithms provided performance gains beyond the simple “aggregated” area as a result of localization being enabled by the networked detectors. We introduce the following three localization-based detection approaches: 1) source-attractor radiation detection (SRD); 2) triangulation-based radiation source detection (TriRSD); and 3) the ratio of square distance-based radiation source detection (ROSD-RSD). We use canonical datasets from Domestic Nuclear Detection Office's intelligence radiation sensors systems tests to assess the performance of these methods. Extensive results demonstrate that SRD outperforms TriRSD and ROSD-RSD, and other existing detection algorithms based on the sequential probability ratio test and maximum likelihood estimation in terms of both false alarm and detection rates.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗

4D tumor centroid tracking using orthogonal 2D dynamic MRI: Implications for radiotherapy planning

Purpose: Current pretreatment, 4D imaging techniques are suboptimal in that they sample breathing motion over a very limited “snapshot” in time. Heretofore, long-duration, 4D motion characterization for radiotherapy planning, margin optimization, and validation have been impractical for safety reasons, requiring invasive markers imaged under x-ray fluoroscopy. To characterize 3D tumor motion and associated variability over durations more consistent with treatments, the authors have developed a practical dynamic MRI (dMRI) technique employing two orthogonal planes acquired in a continuous, interleaved fashion.Methods: 2D balanced steady-state free precession MRI was acquired continuously over 9–14 min at approximately 4 Hz in three healthy volunteers using a commercial 1.5 T system; alternating orthogonal imaging planes (sagittal, coronal, sagittal, etc.) were employed. The 2D in-plane pixel resolution was 2 × 2 mm{sup 2} with a 5 mm slice profile. Simultaneous with image acquisition, the authors monitored a 1D surrogate respiratory signal using a device available with the MRI system. 2D template matching-based anatomic feature registration, or tracking, was performed independently in each orientation. 4D feature tracking at the raw frame rate was derived using spline interpolation.Results: Tracking vascular features in the lung for two volunteers and pancreatic features in one volunteer, the authors have successfully demonstrated this method. Registration error, defined here as the difference between the sagittal and coronal tracking result in the SI direction, ranged from 0.7 to 1.6 mm (1σ) which was less than the acquired image resolution. Although the healthy volunteers were instructed to relax and breathe normally, significantly variable respiration was observed. To demonstrate potential applications of this technique, the authors subsequently explored the intrafraction stability of hypothetical tumoral internal target volumes and 3D spatial probability distribution functions. The surrogate respiratory information allowed the authors to show how this technique can be used to study correlations between internal and external (surrogate) information over these prolonged durations. However, compared against the gold standard of the time stamps in the dMRI frames, the temporal synchronization of the surrogate 1D respiratory information was shown to be likely unreliable.Conclusions: The authors have established viability of a novel and practical pretreatment, 4D tumor centroid tracking method employing a commercially available dynamic MRI sequence. Further developments from the vendor are likely needed to provide a reliably synchronized surrogate 1D respiratory signal, which will likely broaden the utility of this method in the pretreatment radiotherapy planning context.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-F-R-34: Quantitative Perfusion Measurement in Rectal Cancer Using Three Different Pharmacokinetic Models: Implications for Prospective Study Design

Purpose: To compare three different pharmacokinetic models for analysis of dynamic-contrast-enhanced (DCE)-CT data with respect to different acquisition times and location of region of interest. Methods: Eight rectal cancer patients with pre-treatment DCE-CTs were included. The dynamic sequence started 4–10seconds(s) after the injection of contrast agent. The scan included a 110s acquisition with intervals of 40×1s+15×3s+4×6s. An experienced oncologist outlined the tumor region. Hotspots with top-5%-enhancement were also identified. Pharmacokinetic analysis was performed using three different models: deconvolution method, Patlak model, and modified Toft’s model. Perfusion parameters as blood flow (BF), blood volume (BV), mean transit time (MTT), permeability-surface-area-product (PS), volume transfer constant (Ktrans), and flux rate constant (Kep), were compared with respect to different acquisition times of 45s, 65s, 85s and 105s. Both hotspot and whole-volume variances were also assessed. The differences were compared using the Wilcoxon matched-pairs test and Bland-Altman plots. Results: Moderate correlation was observed for various perfusion parameters (r=0.56–0.72, p<0.0001) but the Wilcoxon test revealed a significant difference among the three models (P < .001). Significant differences in PS were noted between acquisitions of 45s versus longer time of 85s or 105s (p<0.05) using Patlak but not with the deconvolution method. In addition, measurements varied substantially between whole-volume vs. hotspot analysis. Conclusion: The radiation dose of DCE-CT was on average 1.5 times of an abdomen/pelvic CT, which is not insubstantial. To take the DCE-CT forward as a biomarker in oncology, prospective studies should be carefully designed with the optimal image acquisition and analysis technique. Our study suggested that: (1) different kinetic models are not interchangeable; (2) a 45s acquisition might not be sufficient for reliable permeability measurement in rectal cancer using Patlak model, but might be achievable using deconvolution method; and (3) local variations existed inside the tumor, and both whole-volume-averaged and local-heterogeneity analysis is recommended for future quantitative studies. This work is supported by the National High-tech R&D program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917), Natural Science Foundation of China (NSFC Grant No. 81201091).

60 APPLIED LIFE SCIENCES↗

Correlations between Texture Profile Analysis and Sensory Evaluation of Cured Largemouth Bass Meat (Micropterus salmoides)

Texture is an important factor in evaluating the quality of aquatic products. To evaluate the texture properties of cured large mouth bass, edible sodium chloride (0, 1.0, 2.0, and 3.0%) was smeared to the bass meat. Texture profile analysis (TPA) and sensory evaluation were performed to evaluate the quality of the cured samples, and the correlations of the indexes in the two methods were analyzed. Two principal components were obtained from the TPA indexes and sensory evaluation indexes, and the cumulative variance contribution rates were 73.87% and 72.99%, respectively. Results from the principal component analysis showed that the main indicators that affected the TPA were gumminess and springiness, while those that affected sensory evaluation were chewiness and adhesiveness. The TPA index and sensory evaluation could be effectively improved when the sodium chloride added to the bass meat was 1%. In the correlation analysis, sensory springiness was negatively correlated with TPA hardness ( P < 0.05 , r = −0.553) but positively correlated with TPA chewiness ( P < 0.05 , r = 0.596). After stepwise regression analysis, the prediction equation between the sensory springiness and TPA hardness was obtained as SSp=5.770−0.002Ha. These results provide a basis for predicting the quality of large mouth bass cured products.

Li, Meijin↗

Virologic outcome among patients receiving antiretroviral therapy at five hospitals in Haiti

Introduction Viral load (VL) assessment is the preferred method for diagnosing and confirming virologic failure for patients on antiretroviral therapy (ART). We conducted a retrospective cross-sectional study to evaluate the virologic suppression rate among patients on ART for 6 months in five hospitals around Port-au-Prince, Haiti. Methods Plasma VL was measured and patients with VL <1,000 copies/mL were defined as virologically suppressed. A second VL test was performed within at least six months of the first test. Factors associated with virologic suppression were analyzed using logistic regression models accounting for site-level clustering using complex survey procedures. Results Data were analyzed for 2,313 patients on ART for six months or longer between July 2013 and February 2015. Among them, 1,563 (67.6%) achieved virologic suppression at the first VL test. A second VL test was performed within at least six months for 718 (31.0%) of the patients. Of the 459 patients with an initial HIV-1 RNA <1,000 copies/mL who had a second VL performed, 394 (85.8%) maintained virologic suppression. Virologic suppression was negatively associated with male gender (adjusted odds ratio [aOR]: 0.80, 95% CI: 0.74– 0.0.86), 23 to 35 months on ART (aOR:0.72[0.54–0.96]), baseline CD4 counts of 201–500 cells/mm 3 and 200 cells/mm 3 or lower (aORs: 0.77 [0.62–0.95] and 0.80 [0.66–0.98], respectively), poor adherence (aOR: 0.69 [0.59–0.81]), and TB co-infection (aOR: 0.73 [0.55–0.97]). Conclusions This study showed that over two-thirds of the patients in this evaluation achieved virologic suppression after six months on ART and the majority of them remained suppressed. These results reinforce the importance of expanding access to HIV-1 viral load testing in Haiti for monitoring ART outcomes.

59 BASIC BIOLOGICAL SCIENCES↗

Add-a-Source Analysis Method for Neutron Coincidence Counting of Waste: Laboratory Exercises

In this session you will setup the INCC code to perform calibration and verification measurements on simulated waste drums using the Waste Drum Assay System (WDAS) detector, which uses the add-a-source (AAS) method. The basis of the AAS method is to measure the change in the counting rate from a small 252 Cf source (~3x10 4 n/s) located outside of the drum and to use this information to correct the count rate from material inside the drum for any changes caused by the matrix inside the drum. The count rate of the material inside the drum is corrected to the empty drum case so that only a single mass calibration curve has to be measured (for the empty drum configuration). In the WDAS system, the AAS neutron source has one location, centered beneath the waste drum. The sample matrix has two primary effects on the neutrons: (1) energy reduction by scattering reactions and (2) neutron absorption of the low-energy neutrons. In general, the counter is designed with an optimum moderator (CH 2 ) thickness to be relatively insensitive to the energy reduction; however, as the hydrogen density in the drum increases, the adsorption process significantly reduces the measured neutron signal.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 5: Utah FORGE Well 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 4: Utah FORGE Well 78B-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 3: Utah FORGE Well 56-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Analysis of Rig Parameter Data Using Drilling Process Modeling Constraints, Volume 1: Summary of Utah FORGE Wells 16A(78)-32, 56-32, 78B-32 and 16B(78)-32

Drill rig parameter measurements are routinely used during deep well construction to monitor and guide drilling conditions for improved performance and reduced costs. While insightful into the drilling process, these measurements are of reduced value without a standard to aid in data evaluation and decision making. In the main body of this work (Volume 1), a method is demonstrated whereby rock reduction model constraints are used to interpret drilling response parameters; the method could be applied in real-time to improve decision-making in the field and to further discern technology performance during post-drilling evaluations. Drilling parameters are evaluated using laboratory-validated rock reduction models for predicting the phenomenological response of drag bits (Detournay and Defourny, 1992) in computational algorithms. The method presented has applicability to development of advanced analytics on future geothermal wells using real-time electronic data recording for improved performance and reduced drilling costs. A drilling cost model is also used to show the tradeoff between rate of penetration and bit life and the influence on interval drilling costs. Details of the bit specifications and performance are cataloged in an independent volume, documented under separate cover, for each of the four wells, and include Volume 2: Utah FORGE 16A(78)-32; Volume 3: Utah FORGE 56-32; Volume 4: Utah FORGE 78B-32 and Volume 5: Utah FORGE 16B(78)-32.

15 GEOTHERMAL ENERGY↗

Investigation of the Effect of Gate Oxide Screening with Adjustment Pulse on Commercial SiC Power MOSFETs

This paper presents a method to recover the negative threshold voltage shift during high field gate oxide screening of 1.2 kV 4H-SiC MOSFETs with an additional adjustment gate voltage pulse. To reduce field failure rates of the MOSFETs in operation, manufacturers perform a screening treatment to remove devices with extrinsic defects in the oxide. Current gate oxide screening procedures are limited to oxide fields at or below ~9 MV/cm for short durations (<1 s), which is not enough to remove all the devices with extrinsic defects. The results show that by implementing a lower field gate pulse, the threshold voltage shift can be partially recovered, and therefore the maximum screening field and time can be increased. However, both the initial screening pulse and the adjustment pulse require careful calibration to prevent significant degradation of the device threshold voltage, on-resistance, interface state density, or intrinsic lifetime. With a well calibrated set of pulses, higher screening fields can be utilized without significantly damaging the devices. This leads to an improvement in the overall screening efficiency of the process, reducing the number of devices with extrinsic oxide defects entering the field, and improving the reliability of the SiC MOSFETs in operation.

42 ENGINEERING↗

Engineering-Scale Integrated Energy System Data Projection Demonstration via the Dynamic Energy Transport and Integration Laboratory

The objective of this study is to demonstrate and validate the Dynamic Energy Transport and Integration Laboratory (DETAIL) preliminary scaling analysis using Modelica language system-code Dymola. The DETAIL preliminary scaling analysis includes a multisystem integral scaling package between thermal-storage and hydrogen-electrolysis systems. To construct the system of scaled equations, dynamical system scaling (DSS) was applied to all governing laws and closure relations associated with the selected integral system. The existing Dymola thermal-energy distribution system (TEDS) facility and high-temperature steam electrolysis (HTSE) facility models in the Idaho National Laboratory HYBRID repository were used to simulate a test case and a corresponding scaled case for integrated system HYBRID demonstration and validation. The DSS projected data based on the test-case simulations and determined scaling ratios were generated and compared with scaled case simulations. The preliminary scaling analysis performance was evaluated, and scaling distortions were investigated based on data magnitude, sequence, and similarity. The results indicated a necessity to change the normalization method for thermal storage generating optimal operating conditions of 261 kW power and mass flow rate of 6.42 kg/s and the possibility of reselecting governing laws for hydrogen electrolysis to improve scaling predictive properties. To enhance system-scaling similarity for TEDS and HTSE, the requirement for scaling validation via physical-facility demonstration was identified.

08 HYDROGEN↗

Nitrogen tetroxide scrubber data analysis

A major difficulty in the analysis of scrubber data is that of separating the physical effects, such as mass transfer, from the physico-chemical effects, such as reaction rates. This is especially true for the absorbtion of nitrogen tetroxide in the various liquids that were tested in the NASA-Kennedy Space Center Hypergolic Toxic Scrubber Program. A fruitful approach to correlating the data for outlet concentrations was to treat the overall absorbtion as a pseudo first-order absorbtion equation. This approach provided a method for normalizing the data to constant inlet concentration, constant sump liquor condition, and constant scrubbing time, and permitted evaluation of the test and fluid parameters that affected both absorbtion rate and scrubbing time. The analysis indicated that scrubber performance may be improved by optimizing liquor concentrations and liquor flowrate distributions.

Simon, E. D.↗