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DOE OSTI2015

Multileaf Collimator Tracking Improves Dose Delivery for Prostate Cancer Radiation Therapy: Results of the First Clinical Trial

Purpose: To test the hypothesis that multileaf collimator (MLC) tracking improves the consistency between the planned and delivered dose compared with the dose without MLC tracking, in the setting of a prostate cancer volumetric modulated arc therapy trial. Methods and Materials: Multileaf collimator tracking was implemented for 15 patients in a prostate cancer radiation therapy trial; in total, 513 treatment fractions were delivered. During each treatment fraction, the prostate trajectory and treatment MLC positions were collected. These data were used as input for dose reconstruction (multiple isocenter shift method) to calculate the treated dose (with MLC tracking) and the dose that would have been delivered had MLC tracking not been applied (without MLC tracking). The percentage difference from planned for target and normal tissue dose-volume points were calculated. The hypothesis was tested for each dose-volume value via analysis of variance using the F test. Results: Of the 513 fractions delivered, 475 (93%) were suitable for analysis. The mean difference and standard deviation between the planned and treated MLC tracking doses and the planned and without-MLC tracking doses for all 475 fractions were, respectively, PTV D{sub 99%} −0.8% ± 1.1% versus −2.1% ± 2.7%; CTV D{sub 99%} −0.6% ± 0.8% versus −0.6% ± 1.1%; rectum V{sub 65%} 1.6% ± 7.9% versus −1.2% ± 18%; and bladder V{sub 65%} 0.5% ± 4.4% versus −0.0% ± 9.2% (P<.001 for all dose-volume results). Conclusion: This study shows that MLC tracking improves the consistency between the planned and delivered doses compared with the modeled doses without MLC tracking. The implications of this finding are potentially improved patient outcomes, as well as more reliable dose-volume data for radiobiological parameter determination.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

UV + Damp Heat Induced Power Losses in Fielded Utility N-Type Si PV Modules

A recent trend in commercial PV modules is a transition to n-type silicon cells, including passivated emitter rear totally diffused (n-PERT), tunnel oxide passivated contact (TOPCon), and silicon heterojunction (SHJ). There is evidence via lab studies that some of these cells are more susceptible to UV induced degradation (UVID), yet there is a lack of confirmation that such degradation occurs in the field. Current IEC standards designed to screen for early module failures require only minimal UV exposure (15 kWh/m2 280-400 nm, ~2-3 months equivalent outdoor exposure). Here, we investigate fielded n-PERT silicon (Si) modules from a commercial utility that show power losses of ~2%/year. We present a comprehensive picture of the physics and chemistry of degradation supported by both module and cell electronic characterization (EL, PL, IV, EQE, and DLIT) and materials-level morphological and chemical analysis (SEM, EDS, XPS, FTIR, and HPLC). All sampled site modules show short circuit current (Isc) and open circuit voltage (Voc) losses when compared to unfielded spares, with the most severely degraded also having losses in fill factor (FF). We identify two different degradation modes contributing to overall power loss: (1) external quantum efficiency (EQE) measurements show losses in the blue range of the spectra, indicative of cell surface recombination losses, and (2) variations in high series resistance (Rs) at the cell level that are correlated with compositional differences in cell metallization. Using unfielded spares, we were able to reproduce Voc, Isc, and EQE losses via a minimum UV stress of 67.5 kWh/m2 (280-400 nm), 4.5x the exposure currently required in IEC 61215-2 (MQT 10). Degradation continued with additional UV dosage equivalent to the fielded modules (405 kWh/m2 total), with power loss leveling out at an average of 6.1%. Subsequent 1000 h of 85% RH/85degrees C damp heat testing showed that cells exposed to UV underwent additional severe series resistance degradation, even those without the susceptible paste composition seen in the field, whereas non-UV exposed cells saw little change. We attribute this to higher concentrations of acetic acid generated on the UV exposed area of the module, leading to degradation of the gridline/cell interface and high Rs. This study is unique in that it reproduces field observed utility scale UVID with an accelerated test and supports the need for standards development for longer UV exposure combined with other stress factors to catch materials interplay within a module package.

14 SOLAR ENERGY↗

DOE OSTI2012

Durability of Polymeric Encapsulation Materials for Concentrating Photovoltaic Systems (Presentation)

Many concentrating photovoltaic (CPV) systems use a polymeric encapsulant to couple and optical component and/or coverglass to the cell. In that location, the encapsulation improves the transmission of concentrated optical flux through interface(s), while protecting the cell from the environment. The durability of encapsulation materials, however, is not well established relative to the desiredservice life of 30 years. Therefore, we have initiated a screen test to identify the field-induced failure modes for a variety of popular PV encapsulation materials. An existing CPV module (with no PV cells present) was modified to accommodate encapsulation specimens. The module (where nominal concentration of solar flux is 500x for the domed-Fresnel design) has been mounted on a tracker inGolden, CO (elevation 1.79 km). Initial results are reported here for 18 months cumulative exposure, including the hottest and coldest months of the past year. Characteristics observed at intervals during that time include: visual appearance, direct and hemispherical transmittance, and mass. Degradation may be assessed from subsequent analysis (including yellowness index and cut-on frequency)relative to the ambient conditions present during field exposure. The fluorescence signature observed of all the silicone specimens is examined here, including possible factors of causation -- the platinum catalyst used in the addition cured materials as well as the primer used to promote adhesion to the quartz substrate and superstrate.

14 SOLAR ENERGY↗

DOE OSTI2017

Towards Cooperative Control of Humanoid Robots for Handling High-Consequence Materials in Gloveboxes - 17291

In this paper, we describe our ongoing work with NASA's Valkyrie humanoid robot and present preliminary results on cooperative control of Valkyrie's hands for performing dexterous manipulation tasks inside gloveboxes commonly found in many nuclear facilities. First, we discuss our human-supervised robot control framework which is based on optimization-based whole-body motion and manipulation controllers. A key aspect of this approach is perception based grasping. We develop a grasping control module for realizing the grasps corresponding to sample tasks such as power, ball, key, pinch, and open palm grasps and their variations. Next, we introduce the notion of motion template library in order to develop generalizable robot grasping and manipulation. Motion template library stores the constraint setting information for the constrained motion planning methods and a framework which can implement the motion template library on different types of robots for accomplishing similar tasks. Motion templates are defined only based on the task requirements. As a result, they can be easily ported to different robot platforms. Lastly, we discuss our multi-modal interfaces designs which include a visual display for improved situational awareness as well as a tactile glove for robot hand control and feedback. Our goal is for the person tele-operating the Valkyrie robot to have better sensing and control than what he or she would have if actually standing at the glovebox doing the work. This improved sensing is comprised of the ability to 'see through' the robot's arms and hands in the gloves and to have an improved sense of touch. The paper concludes with a discussion of our validation strategy. Our success metrics are derived from the completion of a relatively complex experiment to be performed in the glovebox. We evaluate various realistic experiments and use them for task validation and demonstration with Valkyrie. We use speed, time of completion, accuracy, repeatability and reliability rates as success metrics by designing replicable experiments. (authors)

42 ENGINEERING↗

DOE OSTI2012

Durability of Polymeric Encapsulation Materials for Concentrating Photovoltaic Systems (Presentation)

Many concentrating photovoltaic (CPV) systems use a polymeric encapsulant to couple and optical component and/or coverglass to the cell. In that location, the encapsulation improves the transmission of concentrated optical flux through interface(s), while protecting the cell from the environment. The durability of encapsulation materials, however, is not well established relative to the desired service life of 30 years. Therefore, we have initiated a screen test to identify the field-induced failure modes for a variety of popular PV encapsulation materials. An existing CPV module (with no PV cells present) was modified to accommodate encapsulation specimens. The module (where nominal concentration of solar flux is 500x for the domed-Fresnel design) has been mounted on a tracker in Golden, CO (elevation 1.79 km). Initial results are reported here for 18 months cumulative exposure, including the hottest and coldest months of the past year. Characteristics observed at intervals during that time include: visual appearance, direct and hemispherical transmittance, and mass. Degradation may be assessed from subsequent analysis (including yellowness index and cut-on frequency) relative to the ambient conditions present during field exposure. The fluorescence signature observed of all the silicone specimens is examined here, including possible factors of causation -- the platinum catalyst used in the addition cured materials as well as the primer used to promote adhesion to the quartz substrate and superstrate.

14 SOLAR ENERGY↗

DOE OSTI2023

Confidentiality-preserving machine learning algorithms for soft-failure detection in optical communication networks

Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Comparison of breakdown-voltage of contemporary and veteran photovoltaic backsheets

The ability of designated electrically insulating materials in a module, including the backsheet, to act as insulators is a key safety requirement for photovoltaic technology. The recently developed test standards IEC TS 62788-2 (including a method for direct-current breakdown-voltage) and IEC TS 62788-7-2 (for ultraviolet [UV] weathering) are examined for the first time together in this study. Thirty-six contemporary backsheets were compared using the breakdown-voltage test, before and after UV weathering, according to the recent A3 test condition. Twenty-eight backsheets, extracted from a variety of veteran photovoltaic modules, were also examined using the breakdown test. Additional characterizations were performed to interpret the breakdown-voltage results, including: surface and cross-sectional optical microscopy failure analysis; cross-sectional scanning electron (SEM) microscopy with EDS energy-dispersive X-ray spectroscopy (EDX) failure analysis; Fourier-transform infrared spectroscopy (FTIR) to identify the base resin and its chemical integrity; and differential scanning calorimetry (DSC) to identify phase transitions that might adversely affect degradation during weathering. The electrical insulation for the backsheets is discussed relative to: the industry safety requirement; features observed to facilitate the degradation of insulation; the validity of the artificial UV weathering test; the validity of the sheet geometry used for specimens in this study; and the validity of subsequent mechanical testing.

14 SOLAR ENERGY↗

DOE OSTI2016

SU-F-T-212: A Comparison of Treatment Strategies for Intracranial Stereotactic Radiosurgery

Purpose: Stereotactic radiosurgery is an effective and noninvasive treatment for intracranial lesions that uses highly focused radiation beams in a single treatment fraction. The purpose of this study is to investigate the dosimetric differences between the treatment brain metastasis with a proton beam vs. intensity modulated radiation therapy (IMRT). Methods: Ten separate brain metastasis targets where chosen and treatment plans were created for each, using three different strategies: custom proton beam shaping devices, standardized proton beam shaping devices, and IMRT. Each plan was required to satisfy set parameters for providing adequate coverage and minimizing risk to adjacent tissues. The effectiveness of each plan was calculated by comparing the homogeneity index, conformity index, and V12 for each target using a paired one tailed T-test (α=0.05). Specific comparison of the conformity indices was also made using a subcategory containing targets with volume>1cc. Results: There was no significant difference between the homogeneity indices of the three plans (p>0.05), showing that each plan has the capability of adequately covering the targets. There was a statistically significant difference (p<0.01) between the conformity indices of the custom and the standard proton plan, as with the custom proton and IMRT (p<0.01), with custom proton showing stronger conformity to the target in both cases. There was also a statistical difference between the V12 of all three plans (Custom v. Standardized: p=0.02, Custom v. IMRT: p<0.01, Standardized v. IMRT: p<0.01) with custom proton supplying the lowest dose to surrounding tissues. For large targets (volume>1cc) there was no statistical difference between the proton plans and the IMRT treatment for the conformity index. Conclusion: A custom proton plan is the recommended treatment explored in this study as it is the most reliable way of effectively treating the target while sparing the maximum amount of normal tissue.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Coupling an External Plant Code

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) with the aim to develop standalone software to perform the dynamic HRA calculations. Within the HRA, human actions in nuclear power plants (NPPs) are predicated by plant states, and human actions influence the plant. In other words, plant operations are necessarily recursive, and it becomes challenging to model complex human-plant interactions. Consequently, we have linked two software simulations that complement those shortcomings. RELAP5-3D—the Reactor Excursion and Leak Analysis Program (RELAP; Aumiller, Tomlinson, and Bauer 2001) is the foundational thermal-hydraulic software used to model nuclear systems. Using RELAP5-3D, we have simulated the plant operations proceeding according to procedures developed to address emergent situations in NPPs. Plant operations include various actions such as the operator checking plant parameters, as well as actions that are continuously performed over time until a specific parameter reaches certain criteria. That means that HUNTER and RELAP5-3D exchange information with each other and should be carried out simultaneously over time. To simulate plant operations, which represent the actual operator checks of plant parameters and corresponding manual control actions, changes in plant status are identified through simulation and performed according to the criteria and order of the procedure. Thus, the goal of coupling HUNTER with RELAP5-3D is to facilitate synchronous coupling, where human and plant models provide iterative feedback loops that drive the course of actions. The advantage of coupling with RELAP5-3D to serve as the external environment module in HUNTER is the ability to customize the plant model and streamline for particular model applications. In this paper, we will address the key features of the coupling and the coupling structure built to perform the feedback loops.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2016

Degradation in PV Encapsulation Strength of Attachment: An Interlaboratory Study Towards a Climate-Specific Test

Reduced strength of attachment of the encapsulant resulting from the outdoor environment, including ultraviolet (UV) radiation, may decrease photovoltaic (PV) module lifetime by enabling widespread corrosion of internal components. To date, few studies exist showing how the adhesion of PV components varies with environmental stress. We have conducted an interlaboratory experiment to provide an understanding that will be used to develop climatic specific module tests. Factors examined in the study included the UV light source (lamp type), temperature, and humidity to be proposed for use in accelerated aging tests. A poly (ethylene-co-vinyl acetate) (EVA) formulation often used in veteran PV installations was studied using a compressive shear test - to quantify the strength of attachment at the EVA/glass interface. Replicate laminated glass/polymer/glass coupon specimens were weathered at 12 institutions using a variety of indoor chambers or field aging. Shear strength, shear strain, and toughness were measured using a mechanical load-frame for the compressive shear test, with subsequent optical imaging and electron microscopy of the separated surfaces.

14 SOLAR ENERGY↗

DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗

DOE OSTI2024

The "PVLib" of Degradation: PVDeg

The Photovoltaic (PV) industry constantly aims for lower costs through higher-efficiency cells, improved module designs, and improvements in durability. This leads to the use of new materials, designs, and manufacturing processes, and not always with a sufficient amount of durability testing. To help drive down costs there is a desire to create modules that will last for up to 50 years of service life. To accomplish this, every degradation mode and mechanism must be identified and either eliminated or otherwise mitigated. This involves the extrapolation of laboratory results to the field conditions. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. While the basic equations used to model degradation are sometimes very simple, the full analysis involves calculations are cumbersome but ubiquitous for many degradation processes. A simplified, modeling framework to accomplish these repetitive processes will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this talk, we will describe our progress creating the open-source tool PVDeg. This tool can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. PVDeg simplifies many of the common foundational computational operations for obtaining meteorological data and using it to generate a model of the PV deployment. This prediction tool repository also contains various degradation models as well as a library of material parameters suitable for estimating the durability assessment of materials and components. We use an integration pipeline approach that allows us to leverage weather data from the National Solar Radiation Database, and other weather sources, to perform geospatial degradation analysis in the US and worldwide. We hope to become a repository that can be used for weathering and degradation analysis for various applications beyond the PV industry. During the talk, we will provide the PVPMC attendees the opportunity to interact with the tool via a Google Collab tutorial they can run on their phones or laptops.

durability↗

DOE OSTI2023

Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)

This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

Degradation in PV Encapsulant Strength of Attachment: An Interlaboratory Study Towards a Climate-Specific Test

14 SOLAR ENERGY↗

DOE OSTI2012

Towards a framework of nuclear competencies

For the countries considering the introduction of a nuclear energy program, the management of human resources should be a part of the wider integrated management system in order to ensure long term safe and reliable operation. Nuclear energy strategy and approaches to human resources development should take into consideration such fundamental aspects as: development and implementation of a workforce plan, required competencies and qualifications, prerequisites for staffing a nuclear energy program, needed training programs and training facilities, qualification and training requirements. Development of common instruments that respond to the above needs and vision has lead to a new concept of European Credit System for Vocational Education and Training. The European Credit System for Vocational Education and Training (ECVET) is based on definition of 'learning outcomes ' in terms of knowledge, skills and competence, and on identification of portfolios of learning outcomes that allow an individual to prove competencies in a coherent manner. ECVET proposes a common understanding of basic definitions of education and training as well as of the new proposed concepts and it should be recognized by all employers in the EU. In this context, a number of 'Euratom Fission Training Schemes' (EFTS) have been launched in specific areas where a shortage of skilled professionals has been identified. In these schemes the competence building is the result of traditional education plus life-long learning, non-traditional learning, and other forms of educational experiences, relying, in particular, on border-less mobility to get acquainted with various sectors. Each particular Training Scheme should follow a similar path for the achievement of the designed learning outcomes (knowledge, skills, and attitudes). This path to the Training Scheme consists of different activities regarding: definition of training scheme learning outcomes and modules, assessment of prerequisites and student selection, student interview for development of individual training plan, start of the training activities under a specific training scheme. The introduction and recognition of ECVET will lead to a common taxonomy of competencies, and will provide also information about qualifications and units in numerical form, enabling mutual recognition of a training scheme. The description of the learning outcomes to be achieved for qualifying to a specific job profile may follow the analysis phase of the systematic approach to training (SAT). This would ensure a common tool, already used by all trainers. All these steps contribute to establishing of a framework of nuclear competencies recognized and accepted throughout member states. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2012

Novel Assessment of Renal Motion in Children as Measured via Four-Dimensional Computed Tomography

Objectives: Abdominal intensity-modulated radiation therapy and proton therapy require quantification of target and organ motion to optimize localization and treatment. Although addressed in adults, there is no available literature on this issue in pediatric patients. We assessed physiologic renal motion in pediatric patients. Methods and Materials: Twenty free-breathing pediatric patients at a median age of 8 years (range, 2-18 years) with intra-abdominal tumors underwent computed tomography simulation and four-dimensional computed tomography acquisition (slice thickness, 3 mm). Kidneys and diaphragms were contoured during eight phases of respiration to estimate center-of-mass motion. We quantified center of kidney mass mobility vectors in three dimensions: anteroposterior (AP), mediolateral (ML), and superoinferior (SI). Results: Kidney motion decreases linearly with decreasing age and height. The 95% confidence interval for the averaged minima and maxima of renal motion in children younger than 9 years was 5-9 mm in the ML direction, 4-11 mm in the AP direction, and 12-25 mm in the SI dimension for both kidneys. In children older than 9 years, the same confidence interval reveals a widening range of motion that was 5-16 mm in the ML direction, 6-17 mm in the AP direction, and 21-52 mm in the SI direction. Although not statistically significant, renal motion correlated with diaphragm motion in older patients. The correlation between diaphragm motion and body mass index was borderline (r = 0.52, p = 0.0816) in younger patients. Conclusions: Renal motion is age and height dependent. Measuring diaphragmatic motion alone does not reliably quantify pediatric renal motion. Renal motion in young children ranges from 5 to 25 mm in orientation-specific directions. The vectors of motion range from 5 to 52 mm in older children. These preliminary data represent novel analyses of pediatric intra-abdominal organ motion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

Device Voltage Stress from Ground Leakage Current in Medium-Voltage Solid-State Transformer

Grounding related issues are critical for safe and reliable operation of solid-state transformer (SST) in medium-voltage (MV) applications, e.g., solar photovoltaic and energy storage integration, date center, electric vehicle fast charging, etc. This article presents for the first time the issue of additional device voltage stress due to grounding-loop current in current-source SST, using the soft-switching solid-state transformer (S4T) as an example. The S4T features single-stage isolated AC-AC, AC-DC, or DC-DC conversion with full-range ZVS, derived from flyback converter or current-source converter (CSC). However, the flyback operation for CSC-based SST means that magnetizing current flows through the reverse-blocking devices on only one side of the medium-frequency transformer (MFT) at a time. Then, the voltages across the devices, especially those on the other side of the MFT, can be influenced by parasitic current. A parasitic model of a modular S4T (M-S4T) prototype is developed from direct measurements and datasheets. Using the developed parasitic model and equivalent circuits, the causes of the voltage stress are analyzed. A voltage-stress mitigation scheme of connecting additional grounding capacitors is proposed. Damping resistors are also installed to damp out the grounding-loop resonance. A robust parameter design of the proposed scheme is given. The existence of the voltage stress issue and the effectiveness of the proposed scheme are verified experimentally on an MV SiC M-S4T prototype with inherent parameter variations among the five modules in the prototype. Here, both single-module and stacked-module operation are demonstrated during steady state and dynamic conditions up to 4 kV peak.

42 ENGINEERING↗

DOE OSTI2014

SU-C-BRD-01: A Statistical Modeling Method for Quality Control of Intensity- Modulated Radiation Therapy Planning

Purpose: To apply a statistical modeling approach, threshold modeling (TM), for quality control of intensity-modulated radiation therapy (IMRT) treatment plans. Methods: A quantitative measure, which was the weighted sum of violations of dose/dose-volume constraints, was first developed to represent the quality of each IMRT plan. Threshold modeling approach, which is is an extension of extreme value theory in statistics and is an effect way to model extreme values, was then applied to analyze the quality of the plans summarized by our quantitative measures. Our approach modeled the plans generated by planners as a series of independent and identically distributed random variables and described the behaviors of them if the plan quality was controlled below certain threshold. We tested our approach with five locally advanced head and neck cancer patients retrospectively. Two statistics were incorporated for numerical analysis: probability of quality improvement (PQI) of the plans and expected amount of improvement on the quantitative measure (EQI). Results: After clinical planners generated 15 plans for each patient, we applied our approach to obtain the PQI and EQI as if planners would generate additional 15 plans. For two of the patients, the PQI was significantly higher than the other three (0.17 and 0.18 comparing to 0.08, 0.01 and 0.01). The actual percentage of the additional 15 plans that outperformed the best of initial 15 plans was 20% and 27% comparing to 11%, 0% and 0%. EQI for the two potential patients were 34.5 and 32.9 and the rest of three patients were 9.9, 1.4 and 6.6. The actual improvements obtained were 28.3 and 20.5 comparing to 6.2, 0 and 0. Conclusion: TM is capable of reliably identifying the potential quality improvement of IMRT plans. It provides clinicians an effective tool to assess the trade-off between extra planning effort and achievable plan quality. This work was supported in part by NIH/NCI grant CA130814.

60 APPLIED LIFE SCIENCES↗