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DOE OSTI2023

VDiSC: An Open Source Framework for Distributed Smart City Vision and Biometric Surveillance Networks

Recent global growth in the interest of smart cities has led to trillions of dollars of investment toward research and development. These connected cities have the potential to create a symbiosis of technology and society and revolutionize the cost of living, safety, ecological sustainability, and quality of life of societies on a world-wide scale. Some key components of the smart city construct are connected smart grids, self-driving cars, federated learning systems, smart utilities, large-scale public transit, and proactive surveillance systems. While exciting in prospect, these technologies and their subsequent integration cannot be attempted without addressing the potential societal impacts of such a high degree of automation and data sharing. Additionally, the feasibility of coordinating so many disparate tasks will require a fast, extensible, unifying framework. To that end, we propose the Distributed Smart City framework for Vision, or VDiSC. VDiSC serves as a unified biometric API harness that allows for seamless evaluation, deployment, and simple pipeline creation for heterogeneous biometric software. VDiSC additionally provides a fully declarative capability for defining and coordinating custom machine learning and sensor pipelines, allowing the distribution of processes across otherwise incompatible hardware and networks. VDiSC ultimately provides a way to quickly configure, hot-swap, and expand large coordinated or federated systems online without interruptions for maintenance. Because much of the data collected in a smart city contains Personally Identifying Information (PII), VDiSC also provides built-in tools and layers to ensure secure and encrypted streaming, storage, and access of PII data across distributed systems.

Brogan, Joel↗

NASA NTRS1975

ERTS-1 data collection system: Status and performance

The Data Collection System flown on the first Earth Resources Technology Satellite (ERTS-1) relays earth resources data from remotely located in-situ sensors to Goddard Space Flight Center. Data is received at Goddard at least twice each day from every sensor installation and is distributed to users (who operate the sensors and transmitters) by mail and teletype. The system consists of a data formatting and transmitting unit, called the Data Collection Platform (DCP), a receiver and a retransmitter aboard ERTS-1; and receiving, demodulating and decoding equipment located at the Goldstone, California and Goddard data acquisition stations. Data is transmitted from the data acquisition stations to the ERTS Control Center at Goddard, then to the NASA (ERTS) Data Processing Facility (NDPF) where it is processed and distributed to users. Experience to date indicates that the design of the ERTS-1 Data Collection System is adequate for operational use for 50% of the users and, with minor modifications, could meet the requirements of 75%. Some users will have to augment the system by other data collection techniques to meet their operational requirements.

Painter, J. E.↗

DOE OSTI2017

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2011

The power of event-driven analytics in Large Scale Data Processing

FeedZai is a software company specialized in creating high-‐throughput low-‐latency data processing solutions. FeedZai develops a product called "FeedZai Pulse" for continuous event-‐driven analytics that makes application development easier for end users. It automatically calculates key performance indicators and baselines, showing how current performance differ from previous history, creating timely business intelligence updated to the second. The tool does predictive analytics and trend analysis, displaying data on real-‐time web-‐based graphics. In 2010 FeedZai won the European EBN Smart Entrepreneurship Competition, in the Digital Models category, being considered one of the "top-‐20 smart companies in Europe". The main objective of this seminar/workshop is to explore the topic for large-‐scale data processing using Complex Event Processing and, in particular, the possible uses of Pulse in the scope of the data processing needs of CERN. Pulse is available as open-‐source and can be licensed both for non-‐commercial and commercial applications. FeedZai is interested in exploring possible synergies with CERN in high-‐volume low-‐latency data processing applications. The seminar will be structured in two sessions, the first one being aimed to expose the general scope of FeedZai's activities, and the second focused on Pulse itself: 10:00-11:00 FeedZai and Large Scale Data Processing; Introduction to FeedZai; FeedZai Pulse and Complex Event Processing; Demonstration; Use-Cases and Applications; Conclusion and Q&A. 11:00-11:15 Coffee break 11:15-12:30 FeedZai Pulse Under the Hood; A First FeedZai Pulse Application; PulseQL overview; Defining KPIs and Baselines; Conclusion and Q&A. About the speakers Nuno Sebastião is the CEO of FeedZai. Having worked for many years for the European Space Agency (ESA), he was responsible the overall design and development of Satellite Simulation Infrastructure of the agency. Having left ESA to found FeedZai, Nuno is currently responsible for the whole operations of the company. Nuno holds an M.Eng. in Informatics Engineering for the University of Coimbra, and an MBA from the London Business School. Paulo Marques is the CTO of FeedZai, being responsible for product development. Paulo is an Assistant Professor at the University of Coimbra, in the area of Distributed Data Processing, and an Adjunct Associated Professor at Carnegie Mellon, in the US. In the past Paulo lead a large number of projects for institutions like the ESA, Microsoft Research, SciSys, Siemens, among others, being now fully dedicated to FeedZai. Paulo holds a Ph.D. in Distributed Systems from the University of Coimbra.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2016

Resource Prospector Instrumentation for Lunar Volatiles Prospecting, Sample Acquisition and Processing

Lunar Crater↗

NASA NTRS2016

Resource Prospector Instrumentation for Lunar Volatiles Prospecting, Sample Acquisition and Processing

Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP). Resource Prospector is a lunar mission to investigate 'strategic knowledge gaps' (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis. After the RP lander safely delivers the rover to the lunar surface, the science team will guide the rover team on the first traverse plan. The neutron spectrometer (NS) and near infrared (NIR) spectrometer instruments will be used as prospecting tools to guide the traverse path. The NS will map the water-equivalent hydrogen concentration as low as 0.5% by weight to an 80 centimeter depth as the rover traverses the lunar landscape. The NIR spectrometer will measure surficial H2O/OH as well as general mineralogy. When the prospecting instruments identify a potential volatile-rich area during the course of a traverse, the prospect is then mapped out and the most promising location identified. An augering drill capable of sampling to a depth of 100 centimeters will excavate regolith for analysis. A quick assay of the drill cuttings will be made using an operations camera and NIR spectrometer. With the water depth confirmed by this first auguring activity, a regolith sample may be extracted for processing. The drill will deliver the regolith sample to a crucible that will be sealed and heated. Evolved volatiles will be measured by a gas chromatograph-mass spectrometer and the water will be captured and photographed. RP is a solar powered mission, which given the polar location translates to a relatively short mission duration on the order of 4-15 days. This short mission duration drives the concept of operations, instrumentation, and data analysis towards critical real time analysis and decision support. Previous payload field tests have increased the fidelity of the hardware, software, and mission operations. Current activities include a mission level field test to optimize interfaces between the payload and rover as well as better understand the interaction of the science and rover teams during the mission timeline. This paper will include the current status of the science instruments on the payload as well as the integrated field test occurring in fall of 2015. The concept of operations will be discussed, including the real time science and engineering decision-making process based on the critical data from the instrumentation. The path to flight will be discussed with the approach to this ambitious low cost mission.

ISRU↗

NASA NTRS2003

Factors Affecting the Evolution of Hurricane Erin and the Distributions of Hydrometeors: Role of Microphysical Processes

Fine-resolution simulations of Hurricane Erin 2001 are conducted using the Penn State University/National Center for Atmospheric Research mesoscale model version 3.5 to investigate the role of thermodynamic, boundary layer and microphysical processes in Erin's growth and maintenance, and their effects on the horizontal and vertical distributions of hydrometeors. Through comparison against radar, radiometer, and dropsonde data collected during the Convection and Moisture Experiment 4, it is seen that realistic simulations of Erin are obtained provided that fine resolution simulations with detailed representations of physical processes are conducted. The principle findings of the study are as follows: 1) a new iterative condensation scheme, which limits the unphysical increase of equivalent potential temperature associated with most condensation schemes, increases the horizontal size of the hurricane, decreases its maximum rainfall rate, reduces its intensity, and makes its eye more moist; 2) in general, microphysical parameterization schemes with more categories of hydrometeors produce more intense hurricanes, larger hydrometeor mixing ratios, and more intense updrafts and downdrafts; 3) the choice of coefficients describing hydrometeor fall velocities has as big of an impact on the hurricane simulations as does choice of microphysical parameterization scheme with no clear relationship between fall velocity and hurricane intensity; and 4) in order for a tropical cyclone to adequately intensify, an advanced boundary layer scheme (e.g., Burk-Thompson scheme) must be used to represent boundary layer processes. The impacts of varying simulations on the horizontal and vertical distributions of different categories of hydrometeor species, on equivalent potential temperature, and on storm updrafts and downdrafts are examined to determine how the release of latent heat feedbacks upon the structure of Erin. In general, all simulations tend to overpredict precipitation rate and hydrometeor mixing ratios. The ramifications of these findings for quantitative precipitation forecasts (QPFs) of tropical cyclones are discussed.

McFarquhar, Greg M.↗

DOE OSTI2025

Hybrid Quantum Networks with Discrete Polarizations and Continuous Quadrature Variables

Final Scientific/Technical Report for DOE Project DE-SC0022069. Quantum communication and computation systems have evolved along two largely independent paradigms: discrete-variable (DV) systems that encode information in qubits such as photon polarizations or photon-number states, and continuous-variable (CV) systems that encode information in optical field quadratures. Each approach offers distinct advantages—DVs provide low error rates and compatibility with single-photon platforms, while CVs support deterministic operations and efficient quantum state manipulation. A fundamental challenge for building a scalable Quantum Internet lies in interfacing these two regimes into a unified hybrid architecture that can coherently distribute and process quantum information across heterogeneous quantum nodes. This project aims to develop and demonstrate a hybrid optical quantum network that seamlessly integrates DV and CV systems. Specifically, we investigate a new class of hybrid entanglement between the discrete polarizations of single photons and the continuous quadrature variables of optical cat states, overcoming incompatibilities in existing DV–CV demonstrations. Using this new entanglement resource, the team investigates a multi-node hybrid quantum local area network (Q-LAN) testbed capable of DV–CV entanglement generation, swapping, and distribution across fiber links.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS2005

Pre-Launch GOES-R Risk Reduction Activities for the Geostationary Lightning Mapper

The GOES-R Geostationary Lightning Mapper (GLM) is a new instrument planned for GOES-R that will greatly improve storm hazard nowcasting and increase warning lead time day and night. Daytime detection of lightning is a particularly significant technological advance given the fact that the solar illuminated cloud-top signal can exceed the intensity of the lightning signal by a factor of one hundred. Our approach is detailed across three broad themes which include: Data Processing Algorithm Readiness, Forecast Applications, and Radiance Data Mining. These themes address how the data will be processed and distributed, and the algorithms and models for developing, producing, and using the data products. These pre-launch risk reduction activities will accelerate the operational and research use of the GLM data once GOES-R begins on-orbit operations. The GLM will provide unprecedented capabilities for tracking thunderstorms and earlier warning of impending severe and hazardous weather threats. By providing direct information on lightning initiation, propagation, extent, and rate, the GLM will also capture the updraft dynamics and life cycle of convective storms, as well as internal ice precipitation processes. The GLM provides information directly from the heart of the thunderstorm as opposed to cloud-top only. Nowcasting applications enabled by the GLM data will expedite the warning and response time of emergency management systems, improve the dispatch of electric power utility repair crews, and improve airline routing around thunderstorms thereby improving safety and efficiency, saving fuel and reducing delays. The use of GLM data will assist the Bureau of Land Management (BLM) and the Forest Service in quickly detecting lightning ground strikes that have a high probability of causing fires. Finally, GLM data will help assess the role of thunderstorms and deep convection in global climate, and will improve regional air quality and global chemistry/climate modeling. The GLM has a robust design that benefits and improves upon its strong heritage of NASA-developed LEO predecessors, the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS). GLM will have a substantially larger number of pixels within the focal plane, two lens systems, and multiple Real-Time Event Processors REPS for on-board event detection and data compression to provide continuous observations of the Americas and adjacent oceans.

Goodman, S. J.↗

DOE OSTI2011

Residential Real-time Price Response Simulation

The electric industry is gaining experience with innovative price responsive demand pilots and limited roll-outs to customers. One of these pilots is investigating real-time pricing signals to engage end-use systems and local distributed generation and storage in a distributed optimization process. Attractive aspects about the approach include strong scalability characteristics, simplified interfaces between automation devices, and the adaptability to integrate a wide variety of devices and systems. Experience in this nascent field is revealing a rich array of for engineering decisions and the application of complexity theory. To test the decisions, computer simulations are used to reveal insights about design, demand elasticity, and the limits of response (including consumer fatigue). Agent-based approaches lend themselves well in the simulation to modeling the participation and interaction of each piece of equipment on a distribution feeder. This paper discusses rate design and simulation experiences at the distribution feeder level where consumers and their HVAC systems and water heaters on a feeder receive real-time pricing signals.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗

NASA NTRS2009

Acceleration Environment of the International Space Station

Measurement of the microgravity acceleration environment on the International Space Station has been accomplished by two accelerometer systems since 2001. The Microgravity Acceleration Measurement System records the quasi-steady microgravity environment, including the influences of aerodynamic drag, vehicle rotation, and venting effects. Measurement of the vibratory/transient regime, comprised of vehicle, crew, and equipment disturbances, has been accomplished by the Space Acceleration Measurement System-II. Until the arrival of the Columbus Orbital Facility and the Japanese Experiment Module, the location of these sensors, and therefore, the measurement of the microgravity acceleration environment, has been limited to within the United States Laboratory. Japanese Aerospace Exploration Agency has developed a vibratory acceleration measurement system called the Microgravity Measurement Apparatus which will be deployed within the Japanese Experiment Module to make distributed measurements of the Japanese Experiment Module's vibratory acceleration environment. Two Space Acceleration Measurement System sensors from the United States Laboratory will be re-deployed to support vibratory acceleration data measurement within the Columbus Orbital Facility. The additional measurement opportunities resulting from the arrival of these new laboratories allows Principal Investigators with facilities located in these International Space Station research laboratories to obtain microgravity acceleration data in support of their sensitive experiments. The Principal Investigator Microgravity Services project, at NASA Glenn Research Center, in Cleveland, Ohio, has supported acceleration measurement systems and the microgravity scientific community through the processing, characterization, distribution, and archival of the microgravity acceleration data obtained from the International Space Station acceleration measurement systems. This paper summarizes the PIMS capabilities available to the International Space Station scientific community, introduces plans for extending microgravity analysis results to the newly arrived scientific laboratories, and provides summary information for known microgravity environment disturbers.

McPherson, Kevin↗

NASA NTRS1994

The r-process and neutrino-heated supernova ejecta

As a neutron star is formed by the collapse of the iron core of a massive star, its Kelvin-Helmholtz evolution is characterized by the release of gravitational binding energy as neutrinos. The interaction of these neutrinos with heated material above the neutron star generates a hot bubble in an atmosphere that is nearly in hydrostatic equilibrium and heated, after approximately 10 s, to an entropy of S/N(sub AS)k greater than or approximately = 400. The neutron-to-proton ratio for material moving outward through this bubble is set by the balance between neutrino and antineutrino capture on nucleons. Because the electron antineutrino spectrum at this time is hotter than the electron neutrino spectrum, the bubble is neutron-rich (0.38 less than or approximately = Y(sub e) less than or approximately = 0.47). Previous work using a schematic model has shown that these conditions are well suited to the production of heavy elements by the r-process. In this paper we have advanced the numerical modeling of a 20 solar mass 'delayed' supernova explosion to the point that we can follow the detailed evolution of material moving through the bubble at the late times appropiate to r-process nucleosynthesis. The supernova model predicts a final kinetic energy for the ejecta of 1.5 x 10(exp 51) ergs and leaves behind a remnant with a baryon mass of 1.50 solar mass (and a gravitational mass of 1.445 solar mass). We follow the thermodynamic and compositional evolution of 40 trajectories in rho(t), T(t), Y(sub e)(t) for a logarithmic grid of mass elements for the last approximately = 0.03 solar mass to be ejected by the proto-neutron star down to the last less than 10(exp -6) solar mass of material expelled at up to approximately = 18 s after core collapse. We find that an excellent fit to the solar r-process abundance distribution is obtained with no adjustable parameters in the nucleosynthesis calculations. Moreover, the abundances are produced in the quantities required to account for the present Galactic abundances. However, at earlier times, this one-dimensional model ejects too much material with entropies S/N(sub A)k approximately 50 and Y(sub e) approximately 0.46. This leads to an acceptable over production of N = 50 nuclei, particularly Sr-88, Y-89, and Zr-90, relative to their solar abundances. We speculate on various means to avoid the early overproduction and/or ejection of N = 50 isotonic nuclei while still producing and ejecting the correct amount of r-process material.

Woosley, S. E.↗

NASA NTRS2010

Constraints on Mercury's Na Exosphere: Combined MESSENGER and Ground-Based Data

We have used observations of sodium emission obtained with the McMath-Pierce solar telescope and MESSENGER's Mercury Atmospheric and Surface Composition Spectrometer (MASCS) to constrain models of Mercury's sodium exosphere, The distribution of sodium in Mercury's exosphere during the period January 12-15. 2008. was mapped using the McMath-Pierce solar telescope with the 5" X 5" image slicer to observe the D-line emission. On January 14, 2008, the Ultraviolet and Visible Spectrometer (UVVS) channel on MASCS sampled the sodium in Mercury's anti-sunward tail region. We find that the bound exosphere has an equivalent temperature of 900-1200 K, and that this temperature can be achieved if the sodium is ejected either by photon-stimulated desorption (PSD) with a 1200 K Maxwellian velocity distribution, or by thermal accommodation of a hotter source. We were not able to discriminate between the two assumed velocity distributions of the ejected particles for the PSD. but the velocity distributions require different values of the thermal accommodation coefficient and result in different upper limits on impact vaporization, We were able to place a strong constraint on the impact vaporization rate that results in the release of neutral Na atoms with an upper limit of 2.1 x 10(exp 6) sq cm/s, The variability of the week-long ground-based observations can be explained by variations in the sources, including both PSD and ion-enhanced PSD, as well as possible temporal enhancements in meteoroid vaporization. Knowledge of both dayside and anti-sunward tail morphologies and radiances are necessary to correctly deduce the exospheric source rates, processes, velocity distribution, and surface interaction.

Mouawad, Nelly↗

DOE OSTI2018

Cost Recovery for Standby and Ancillary Services for Distributed Generation: Considerations for New Mexico

A New Mexico statute allows investor-owned utilities to recover costs of “standby and ancillary services” resulting from distributed generation (DG). In attempting to do so, it is important to recognize both the physical and economic impacts, positive and negative, that distributed generation creates. Distributed generation has different impacts on ancillary and standby services depending on the location, capacity, and production patterns of the systems. Low penetrations of small distributed generation systems will not create significant contingencies for utilities. System impact of fluctuations in DG production may be no larger than normal fluctuations caused by customer demand, such as an air conditioner cycling. Higher penetrations and large DG system may produce noticeable impacts; so magnitude is critical when determining potential additional recoverable utility costs. Understanding DG impact on ancillary services is a relatively new and emerging area of study and as such there are not well-established formulas or protocols. Discretion is required. A hosting capacity analysis can help determine how much DG can be implemented before the impacts become substantive. Standby rates are traditionally used for large industrial generators or combined heat and power systems and threshold system size levels are often used in determining applicability of standby rates. System size thresholds may also be appropriate for standby rates and DG. Relatively small, geographically diverse DG systems are unlikely to create a noticeable coincident outage, so developing a standby charge based on assumed coincidence may not be appropriate. Individual lines and feeders may have considerable excess capacity during coincident outages, or they may be fully utilized and facing upgrades in the near future, which could vary over time. Understanding specific events that create concern for utilities is critical to developing an appropriate rate mechanism (e.g., single residential or community system outage, cascading event, clouds, eclipse). Any modeling or studies of the grid should also recognize the unique situation created when DG is coupled with a smart inverter or storage. These devices change the value proposition and can help mitigate some of the voltage and ramping issues DG can pose for a utility. Utilities can recover their fixed costs in a variety of ways, and some are better suited for DG than others. Beyond charging for standby and ancillary services, other options include fixed customer charges, demand charges, minimum bills, time-of-use rates and updated net energy-metering policies. Studies and analyses of the specific impacts that DG has on the grid should inform utilities’ decision-making process because distributed generation creates both costs and benefits for the grid. Any charge specific to DG customers should be backed up with analysis. At the heart of this conversation is utilities attempting to recover fixed costs. Allowing utilities to indiscriminately recover all stranded fixed costs can negatively affect long-term market efficiency by blunting utility incentives to lower costs and acting as a barrier to entry and exit. The current status of New Mexico’s grid, impending infrastructure updates, and likely customer adoption patterns for DG (backed up by transparent analysis) should remain at the forefront when considering charges for standby and ancillary services. Recognizing that utility regulation is largely a reactive process, it is recommended that applications for DG related standby or ancillary services cost recovery mechanisms be thoroughly reviewed by an experienced economist. If the commission has no such skill set on staff, one might be hired.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1996

Design of a Subscale Propellant Slag Evaluation Motor Using Two-Phase Fluid Dynamic Analysis

Small pressure perturbations in the Space Shuttle Reusable Solid Rocket Motor (RSRM) are caused by the periodic expulsion of molten aluminum oxide slag from a pool that collects in the aft end of the motor around the submerged nozzle nose during the last half of motor operation. It is suspected that some motors produce more slag than others due to differences in aluminum oxide agglomerate particle sizes that may relate to subtle differences in propellant ingredient characteristics such as particle size distributions or processing variations. A subscale motor experiment was designed to determine the effect of propellant ingredient characteristics on the propensity for slag production. An existing 5 inch ballistic test motor was selected as the basic test vehicle. The standard converging/diverging nozzle was replaced with a submerged nose nozzle design to provide a positive trap for the slag that would increase the measured slag weights. Two-phase fluid dynamic analyses were performed to develop a nozzle nose design that maintained similitude in major flow field features with the full scale RSRM. The 5 inch motor was spun about its longitudinal axis to further enhance slag collection and retention. Two-phase flow analysis was used to select an appropriate spin rate along with other considerations, such as avoiding bum rate increases due to radial acceleration effects. Aluminum oxide particle distributions used in the flow analyses were measured in a quench bomb for RSRM type propellants with minor variations in ingredient characteristics. Detailed predictions for slag accumulation weights during motor bum compared favorably with slag weight data taken from defined zones in the subscale motor and nozzle. The use of two-phase flow analysis proved successful in gauging the viability of the experimental program during the planning phase and in guiding the design of the critical submerged nose nozzle.

Whitesides, R. Harold↗

DOE OSTI2011

Dosimetric Impact of Interfraction Catheter Movement in High-Dose Rate Prostate Brachytherapy

Purpose: To evaluate the impact of interfraction catheter movement on dosimetry in prostate high-dose-rate (HDR) brachytherapy. Methods and Materials: Fifteen patients were treated with fractionated HDR brachytherapy. Implants were performed on day 1 under transrectal ultrasound guidance. A computed tomography (CT) scan was performed. Inverse planning simulated annealing was used for treatment planning. The first fraction was delivered on day 1. A cone beam CT (CBCT) was performed on day 2 before the second fraction was given. A fusion of the CBCT and CT was performed using intraprostatic gold markers as landmarks. Initial prostate and urethra contours were transferred to the CBCT images. Bladder and rectum contours were drawn, and catheters were digitized on the CBCT. The planned treatment was applied to the CBCT dataset, and dosimetry was analyzed and compared to the initial dose distribution. This process was repeated after a reoptimization was performed, using the same constraints used on day 1. Results: Mean interfraction catheter displacement was 5.1 mm. When we used the initial plan on day 2, the mean prostate V100 (volume receiving 100 Gy or more) decreased from 93.8% to 76.2% (p < 0.01). Rectal V75 went from 0.75 cm{sup 3} to 1.49 cm{sup 3} (p < 0.01). A reoptimization resulted in a mean prostate V100 of 88.1%, closer to the initial plan (p = 0.05). Mean rectal V75 was also improved with a value of 0.59 cm{sup 3}. There was no significant change in bladder and urethra dose on day 2. Conclusions: A mean interfraction catheter displacement of 5.1 mm results in a significant decrease in prostate V100 and an increase in rectum dose. A reoptimization before the second treatment improves dose distribution.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

Explicitly Accounting for Multiple Spatial Scales in Data Informing Kd Distribution Development - 18414

This work provides an example of incorporating information about spatial scale into input parameter distribution development for probabilistic performance assessment (PA) models and highlights the importance of having an interdisciplinary team working together in the distribution development process. The novel approach is demonstrated for contaminant partitioning coefficients for water/rock (Kds), providing a specific context for discussing the approach and challenges, but the strategy is general and applies to many other PA model inputs. In this example, a PA model of a radioactive waste disposal site is assumed to have large cells representing spatial scales of up to thousands of square meters in area and several to tens of meters in depth. Spatial variability in Kds is expected to occur at scales much smaller than the units in the model domain over which values are applied, and therefore values are intended to represent possible averages over the modeled volume (i.e., spatial scale represented by a PA model cell). Information about possible Kd values for each material category comes from a variety of literature sources, and the reported results used to inform the distribution are available at a wide range of scales (e.g., individual batch experiment results from small-scale samples, averages based on samples collected over site-scales, averages based on samples from large regions, etc.). Effectively addressing the mismatch in spatial scale between available information and the PA Model is a challenge within PA distribution development and it takes effort from database managers, subject matter experts, modelers, and statisticians. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗