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At least 883 records · Page 49

EC Transmission Line Risk Identification and Mitigation Analysis

The purpose of this document is to assist in evaluating and planning for the cost, schedule, and technical project risks associated with the delivery and operation of the EC (Electron cyclotron) transmission line system. In general, the major risks that are anticipated to be encountered during the project delivery phase associated with the implementation of the Procurement Arrangement for the EC transmission line system are associated with: (1) Undefined or changing requirements (e.g., functional or regulatory requirements); (2) Underperformance of prototype, first unit, or production components during testing; (3) Unavailability of qualified vendors for critical components Technical risks associated with the design and operation of the system are also identified.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Modification and validation of an analytical source model for external beam radiotherapy Monte Carlo dose calculations

Purpose: A dose calculation tool, which combines the accuracy of the dose planning method (DPM) Monte Carlo code and the versatility of a practical analytical multisource model, which was previously reported has been improved and validated for the Varian 6 and 10 MV linear accelerators (linacs). The calculation tool can be used to calculate doses in advanced clinical application studies. One shortcoming of current clinical trials that report dose from patient plans is the lack of a standardized dose calculation methodology. Because commercial treatment planning systems (TPSs) have their own dose calculation algorithms and the clinical trial participant who uses these systems is responsible for commissioning the beam model, variation exists in the reported calculated dose distributions. Today’s modern linac is manufactured to tight specifications so that variability within a linac model is quite low. The expectation is that a single dose calculation tool for a specific linac model can be used to accurately recalculate dose from patient plans that have been submitted to the clinical trial community from any institution. The calculation tool would provide for a more meaningful outcome analysis. Methods: The analytical source model was described by a primary point source, a secondary extra-focal source, and a contaminant electron source. Off-axis energy softening and fluence effects were also included. The additions of hyperbolic functions have been incorporated into the model to correct for the changes in output and in electron contamination with field size. A multileaf collimator (MLC) model is included to facilitate phantom and patient dose calculations. An offset to the MLC leaf positions was used to correct for the rudimentary assumed primary point source. Results: Dose calculations of the depth dose and profiles for field sizes 4 × 4 to 40 × 40 cm agree with measurement within 2% of the maximum dose or 2 mm distance to agreement (DTA) for 95% of the data points tested. The model was capable of predicting the depth of the maximum dose within 1 mm. Anthropomorphic phantom benchmark testing of modulated and patterned MLCs treatment plans showed agreement to measurement within 3% in target regions using thermoluminescent dosimeters (TLD). Using radiochromic film normalized to TLD, a gamma criteria of 3% of maximum dose and 2 mm DTA was applied with a pass rate of least 85% in the high dose, high gradient, and low dose regions. Finally, recalculations of patient plans using DPM showed good agreement relative to a commercial TPS when comparing dose volume histograms and 2D dose distributions. Conclusions: A unique analytical source model coupled to the dose planning method Monte Carlo dose calculation code has been modified and validated using basic beam data and anthropomorphic phantom measurement. While this tool can be applied in general use for a particular linac model, specifically it was developed to provide a singular methodology to independently assess treatment plan dose distributions from those clinical institutions participating in National Cancer Institute trials.

60 APPLIED LIFE SCIENCES↗

CT-Guided Radioactive {sup 125}I Seed Implantation Therapy of Symptomatic Retroperitoneal Lymph Node Metastases

Purpose: This study explored the clinical efficacy of CT-guided radioactive {sup 125}I seed implantation in treating patients with symptomatic retroperitoneal lymph node metastases. Methods: Twenty-five patients with pathologically confirmed malignant tumors received CT-guided radioactive {sup 125}I seed implantation to treat metastatic lymph nodes. The diameter of the metastatic lymph nodes ranged from 1.5 to 4.5 cm. Treatment planning system (TPS) was used to reconstruct the three-dimensional image of the tumor and then calculate the corresponding quantity and distribution of {sup 125}I seeds. Results: Follow-up period for this group of patients was 2–30 months, and median time was 16 months. Symptoms of refractory pain were significantly resolved postimplantation (P < 0.05), and Karnofsky score rose dramatically (P < 0.05). Most patients reported pain relief 2–5 days after treatment. Follow-up imaging studies were performed 2 months later, which revealed CR in 7 patients, PR in 13 patients, SD in 3 patients, and PD in 2 patients. The overall effective rate (CR + PR) was 80 %. Median survival time was 25.5 months. Seven patients died of recurrent tumor; 16 patients died of multiorgan failure or other metastases. Two patients survived after 30 months follow-up. Two patients reported localized skin erythema 1 week postimplantation, which disappeared after topical treatment. Conclusions: CT-guided radioactive {sup 125}I seed implantation, which showed good palliative pain relief with acceptable short-term effects, has proved in our study to be a new, safe, effective, and relatively uncomplicated treatment option for symptomatic retroperitoneal metastatic lymph nodes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Investigating the effects of cooperative transmission expansion planning on grid performance during heat waves with varying spatial scales

There is growing recognition of the advantages of interregional transmission capacity to decarbonize electricity grids. A less explored benefit is potential performance improvements during extreme weather events. This study examines the impacts of cooperative transmission expansion planning using an advanced modeling chain to simulate power grid operations of the United States Western Interconnection in 2019 and 2059 under different levels of collaboration between transmission planning regions. Two historical heat waves in 2019 with varying geographical coverage are replayed under future climate change in 2059 to assess the transmission cooperation benefits during grid stress. The results show that cooperative transmission planning yields the best outcomes in terms of reducing wholesale electricity prices and minimizing energy outages both for the whole interconnection and individual transmission planning regions. Compared to individual planning, cooperative planning reduces wholesale electricity prices by 64.3 % and interconnection-wide total costs (transmission investments + grid operations) by 34.6 % in 2059. It also helps decrease greenhouse gas emissions by increasing renewable energy utilization. However, the benefits of cooperation diminish during the widespread heat wave when all regions face extreme electricity demand due to higher space cooling needs. Despite this, cooperative transmission planning remains advantageous, particularly for California Independent System Operator with significant diurnal solar generation capacity. This study suggests that cooperation in transmission planning is crucial for reducing costs and increasing reliability both during normal periods and extreme weather events. It highlights the importance of optimizing the strategic investments to mitigate challenges posed by wider-scale extreme weather events of the future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantifying Value and Representing Competitiveness of Electricity System Technologies in Economic Models

Evaluating competition between electricity technologies is challenging because it depends on both their costs and their values. While technology costs can typically be estimated from projections of the cost components - capital, fuel, and O&M - estimating a technology's value is more complex due to its dependence on its contributions to multiple different grid services, each with prices that can vary substantially over space and time. In this work, using an electricity model of the contiguous United States, we develop relationships between relative value and share of total generation for major electricity generation technologies which, when paired with projections of technology costs, can be used to estimate technology competitiveness. We identify significant differences in the relationship between relative value and generation share for variable renewable energy (VRE) and non-VRE sources, but we demonstrate that all technologies require consideration of their dynamic values (in addition to cost) when evaluating competitiveness. In addition, we demonstrate that relative value of a technology is substantially impacted by not only its own generation share but also other aspects of the system state, in particular the mix of other technologies present in the system. Finally, we use the developed relative value relationships in combination with projections of future technology costs in a coarse resolution model that competes technologies based on a comprehensive competitiveness metric: profitability-adjusted LCOE (PLCOE). We show that this simple representation of technology competition approximately recovers the generation mix from a detailed model, which is not possible using LCOE alone. Such an approach can be used to improve the representation of technology competition in coarse-resolution models such as integrated assessment models, for which simplified metrics are often needed.

electricity model↗

SU-E-CAMPUS-T-01: Analysis of the Precision of Patient Set-Up, and Fidelity of the Delivered Dose Distribution in Proton Therapy of Ocular Tumors

Purpose: To quantify daily set-up variations in fractionated proton therapy of ocular melanomas, and to assess the effect on the fidelity of delivered distribution to the plan. Methods: In a typical five-fraction course, daily set-up is achieved by matching the position of fiducial markers in orthogonal radiographs to the images generated by treatment planning program. A patient maintains the required gaze direction voluntarily, without the aid of fixation devices. Confirmation radiographs are acquired to assess intrafractional changes. For this study, daily radiographs were analyzed to determine the daily iso-center position and apparent gaze direction, which were then transferred to the planning system to calculate the dose delivered in individual fractions, and accumulated dose for the entire course. Dose-volume metrics were compared between the planned and accumulated distributions for the tumor and organs at risk, for representative cases that varied by location within the ocular globe. Results: The analysis of the first set of cases (3 posterior, 3 transequatorial and 4 anterior tumors) revealed varying dose deviation patterns, depending on the tumor location. For anterior and posterior tumors, the largest dose increases were observed in the lens and ciliary body, while for the equatorial tumors, macula, optic nerve and disk, were most often affected. The iso-center position error was below 1.3 mm (95%-confidence interval), and the standard deviation of daily polar and azimuthal gaze set-up were 1.5 and 3 degrees, respectively. Conclusion: We quantified interfractional and intrafractional set-up variation, and estimated their effect on the delivered dose for representative cases. Current safety margins are sufficient to maintain the target coverage, however, the dose delivered to critical structures often deviates from the plan. The ongoing analysis will further explore the patterns of dose deviation, and may help to identify particular treatment scenarios which are at a higher risk for such deviations.

60 APPLIED LIFE SCIENCES↗

SU-E-T-85: Comparison of Treatment Plans Calculated Using Ray Tracing and Monte Carlo Algorithms for Lung Cancer Patients Having Undergone Radiotherapy with Cyberknife

Purpose: The latest publications indicate that the Ray Tracing algorithm significantly overestimates the dose delivered as compared to the Monte Carlo (MC) algorithm. The purpose of this study is to quantify this overestimation and to identify significant correlations between the RT and MC calculated dose distributions. Methods: Preliminary results are based on 50 preexisting RT algorithm dose optimization and calculation treatment plans prepared on the Multiplan treatment planning system (Accuray Inc., Sunnyvale, CA). The analysis will be expanded to include 100 plans. These plans are recalculated using the MC algorithm, with high resolution and 1% uncertainty. The geometry and number of beams for a given plan, as well as the number of monitor units, is constant for the calculations for both algorithms and normalized differences are compared. Results: MC calculated doses were significantly smaller than RT doses. The D95 of the PTV was 27% lower for the MC calculation. The GTV and PTV mean coverage were 13 and 39% less for MC calculation. The first parameter of conformality, as defined as the ratio of the Prescription Isodose Volume to the PTV Volume was on average 1.18 for RT and 0.62 for MC. Maximum doses delivered to OARs was reduced in the MC plans. The doses for 1000 and 1500 cc of total lung minus PTV, respectively were reduced by 39% and 53% for the MC plans. The correlation of the ratio of air in PTV to the PTV with the difference in PTV coverage had a coefficient of −0.54. Conclusion: The preliminary results confirm that the RT algorithm significantly overestimates the dosages delivered confirming previous analyses. Finally, subdividing the data into different size regimes increased the correlation for the smaller size PTVs indicating the MC algorithm improvement verses the RT algorithm is dependent upon the size of the PTV.

60 APPLIED LIFE SCIENCES↗

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗

Modeling Smart Microgrids for the Developing World with Probabilistic Supply and Demand Inputs

Developing world microgrids often balance insufficient supply with growing, unpredictable demand. Deterministic and probabilistic simulators exist to model these microgrids, and each focuses on different technical aspects. With the addition of smart meters into microgrids, monitoring and control is now available at high granularity, which enriches microgrid planning and operation. This research is designing a new simulator to model smart microgrids with discrete probability distributions as supply and demand inputs. In our model, smart meters allow real-time power clipping for demand side management, effectively smoothing the system load curve as needed. To compare clipping schemes for grid operation and generation mixes for planning, we aggregate inputs by convolution then compute expected energy sold and probability of avoiding power cuts. The simulator plots these values for different combinations of power clipping threshold and number of customers clipped.

13 HYDRO ENERGY↗

SU-E-T-626: Accuracy of Dose Calculation Algorithms in MultiPlan Treatment Planning System in Presence of Heterogeneities

Purpose: Advanced stereotactic radiotherapy (SRT) treatments require accurate dose calculation for treatment planning especially for treatment sites involving heterogeneous patient anatomy. The purpose of this study was to evaluate the accuracy of dose calculation algorithms, Raytracing and Monte Carlo (MC), implemented in the MultiPlan treatment planning system (TPS) in presence of heterogeneities. Methods: First, the LINAC of a CyberKnife radiotherapy facility was modeled with the PENELOPE MC code. A protocol for the measurement of dose distributions with EBT3 films was established and validated thanks to comparison between experimental dose distributions and calculated dose distributions obtained with MultiPlan Raytracing and MC algorithms as well as with the PENELOPE MC model for treatments planned with the homogenous Easycube phantom. Finally, bones and lungs inserts were used to set up a heterogeneous Easycube phantom. Treatment plans with the 10, 7.5 or the 5 mm field sizes were generated in Multiplan TPS with different tumor localizations (in the lung and at the lung/bone/soft tissue interface). Experimental dose distributions were compared to the PENELOPE MC and Multiplan calculations using the gamma index method. Results: Regarding the experiment in the homogenous phantom, 100% of the points passed for the 3%/3mm tolerance criteria. These criteria include the global error of the method (CT-scan resolution, EBT3 dosimetry, LINAC positionning …), and were used afterwards to estimate the accuracy of the MultiPlan algorithms in heterogeneous media. Comparison of the dose distributions obtained in the heterogeneous phantom is in progress. Conclusion: This work has led to the development of numerical and experimental dosimetric tools for small beam dosimetry. Raytracing and MC algorithms implemented in MultiPlan TPS were evaluated in heterogeneous media.

60 APPLIED LIFE SCIENCES↗

Cumulus: NASA's Cloud Based Distributed Active Archive Center Prototype

NASAs Earth Science Data System (ESDS) Program serves as a central cog in order to facilitate the implementation of NASA's Earth Science strategic plan. Since 1994, the ESDS Program has committed to the full and open sharing of Earth science data obtained from NASA instruments to all users. One of the key responsibilities of the ESDS Program is to continuously evolve the entire data and information system to maximize returns on the collected NASA data. An independent review was conducted in 2015 to holistically review the EOSDIS in order to identify gaps. The review recommendations were to investigate two areas: one, whether commercial cloud providers offer potential for storage, processing, and operational efficiencies, and two, the potential development of new data access and analysis paradigms. In response, ESDS has initiated several prototypes investigating the advantages and risks of leveraging cloud computing. This paper describes one such prototyping activity named Cumulus. Cumulus is being designed and developed as a "native" cloud-based data ingest, archive and management system that can be used for all future NASA Earth science data streams. Cumulus will foster design of new analysisvisualization tools that can leverage collocated data from all of the distributed DAACs as well as elastic cloud computing resources.

Earth Science Informatics↗

NASA and the U.S. climate program - A problem in data management

NASA's contribution to the total data base for the National Climate Plan will be to produce climate data sets from its experimental space observing systems and to maximize the value of these data for climate analysis and prediction. Validated data sets will be provided to NOAA for inclusion into their overall diagnostic data base. NASA data management for the Climate Plan will involve: (1) cataloging and retrieval of large integrated and distributed data sets upon user demand, and (2) the storage equivalent of 100,000 digital data tapes. It will be the largest, most complex data system ever developed by NASA

Quann, J. J.↗

Technology solutions to mitigate electricity cost for electric vehicle DC fast charging

Widespread adoption of alternative fuel vehicles is being hindered by high vehicle costs and refueling or range limitations. For plug-in electric vehicles, direct-current fast charging (DCFC) is proposed as a solution to support long-distance travel and relieve range anxiety. However, DCFC has also been shown to be potentially more expensive compared to residential or workplace charging. In particular, electricity demand charges can significantly impact electricity cost for fast charging applications. Here we explore technological solutions that can help reduce the electricity cost for electric vehicle fast charging. In particular, we consider thousands of electricity rates available in the United States and real-world vehicle charging load scenarios to assess opportunities to reduce the cost of DCFC by deploying solar photovoltaics (PV) panels and energy storage (battery), and implementing a co-location configuration where a DCFC station is connected to an existing meter within a commercial building. Results show that while the median electricity cost across more than 7000 commercial retail rates remains less than $0.20/kWh for all charging load scenarios considered, cost varies greatly, and some locations do experience significantly higher electricity cost. Co-location is almost always economically viable to mitigate fixed cost and demand charges, but the relative benefit of co-locating diminishes as station size and utilization increase. Energy storage alone can help mitigate demand charges and is more effective at reducing costs for 'peaky' or low-utilization loads. On the other hand, PV systems primarily help mitigate energy charges, and are more effective for loads that are more correlated with solar production, even in areas with lower solar resource. PV and energy storage can deploy synergistically to provide cost reductions for DCFC, leveraging their ability to mitigate demand and energy charges.

25 ENERGY STORAGE↗

Influence of building heat distribution temperatures on the energy performance and sizing of 5th generation district heating and cooling networks

This paper investigates the energy performance and sizing criteria of 5th generation district heating and cooling (5GDHC) networks as a function of the heat distribution temperature in the building systems connected to the district network. An energy simulation model of a 5GDHC network was developed in Modelica for a case study located in Denmark. Calculations were carried out for four different building heating systems. Simulation results show that reducing the heat distribution temperatures from 70 °C to 23 °C leads to around 40% annual electric energy savings (from 10.4 kWh/m 2 to 6.2 kWh/m 2 ) for the operation of the heat pumps. Heat distribution temperatures of 23 °C cause higher water mass flow rates through the network, leading to annual electric energy consumption for the circulation pumps that are almost doubled (from 0.16 kWh/m 2 to 0.3 kWh/m 2 ) compared to the reference case at 70 °C. Furthermore, the paper discusses how the results obtained from the Danish case study can be generalized and applied to other cases using a simplified mathematical approach. In conclusion, it is found that about 1.5% of electric energy savings can be achieved for each temperature degree reduction in the heat distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗

Opportunities for Integrating Electric and Gas Planning

Growing demand for electricity in buildings is creating new opportunities and challenges for electric and natural gas planning. To date, electric and gas planning processes have largely been siloed, and only a few jurisdictions have started to examine how these two processes could be linked together. The report explores the current state of electric and gas system planning, and the benefits and challenges of integrating these planning processes. We frame the characteristics of an integrated electric and gas distribution planning process and identify indicators of progress toward the characteristics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Assess program: Interactive data management systems for airborne research

Two data systems were developed for use in airborne research. Both have distributed intelligence and are programmed for interactive support among computers and with human operators. The C-141 system (ADAMS) performs flight planning and telescope control functions in addition to its primary role of data acquisition; the CV-990 system (ADDAS) performs data management functions in support of many research experiments operating concurrently. Each system is arranged for maximum reliability in the first priority function, precision data acquisition.

Munoz, R. M.↗