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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Extended Accelerated Stress Testing (EAST) of Glass/Glass, Glass/Backsheet and Glass/Transparent Backsheet PV Modules: Influence of EVA and POE Encapsulants: Preprint

This paper presents the indoor extended accelerated stress testing (EAST) results of glass/glass (GG), glass/backsheet (GB) and glass/transparent backsheet (GT) modules having identical cells and two different encapsulant types, ethyl-vinyl-acetate (EVA) and polyolefin-elastomer (POE). Six 4-cell modules having the above-mentioned construction combinations were subjected to extended ultraviolet (UV; 600 kWh/m2), damp-heat (DH; 2000 hours) and thermal-cycling (TC; 600 cycles) tests. The post-stress UV fluorescent imaging, electroluminescent imaging, reflectance spectrophotometry and colorimetry results indicated that the grid finger degradation and encapsulant browning are slightly higher in the GG modules compared to the GB modules. The post-stress IV test results indicated, in general, that the GG/EVA modules tend to perform inferior to the GG/POE modules with the EAST evaluation.

EVA↗
DOE OSTI2013

Measurements and Characterization (Revised) (Fact Sheet)

Capabilities fact sheet for the National Center for Photovoltaics: Measurements and Characterization that includes scope, core competencies and capabilities, and contact/web information for Analytical Microscopy, Electro-Optical Characterization, Surface Analysis, and Cell and Module Performance.

14 SOLAR ENERGY↗
DOE OSTI2017

Code eOMEGA - Decommissioning Costing of Nuclear Facilities Based on the ISDC - 17230

The paper is focused on the presentation of the development process, calculation procedure and main features of the eOMEGA code used for decommissioning costing of nuclear facilities. The methodology for decommissioning cost calculation implemented to the eOMEGA code is fully in line with the international recommendations, best practices and is completely based on the ISDC - The International Structure for Decommissioning Costing (ISDC) of Nuclear Installation. ISDC represents the standard and common platform for presenting the results of the cost estimates for decommissioning projects related to any type of nuclear facility. The main goal of the eOMEGA costing code is to provide the ISDC based flexible, open, modern and user-friendly tool for transparent and reliable decommissioning costing for any type of nuclear facility with any systems, structures and radiological situation at the end of the operational period. Moreover, the eOMEGA decommissioning costing code is intended to be one of the modules of the universal eOMEGA platform which should cover also the other activities within the back-end of nuclear power engineering e.g. decommissioning funding, back end of nuclear fuel cycle, site remediation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Operational Probabilistic Tools for Solar Uncertainty (OPTSUN) (Final Project Report for DOE Solar Forecasting II Project)

Increasing levels of solar PV can challenge system operations and may require novel methods to operate the power system reliably and efficiently. Power system operating plans generally use deterministic forecasts, in which the variable energy resources are represented by the expected value for each interval of the decision horizon. Probabilistic forecasts are relatively new but have the potential to address the shortfalls of deterministic forecasts. However, understanding how best to use such forecasts is still a key gap in industry and was the focus of this project. The project had three workstreams. In a forecasting workstream, improvements were made to baseline probabilistic forecasts using a number of new approaches such as machine learning methods and improved input data. In a design workstream, advanced simulation tools used these forecasts to investigate newly proposed reserve determination methods. Lastly, in a demonstration workstream a scheduling management platform (SMP) was developed to leverage probabilistic forecasts in a modular and customizable manner. In order to study the benefits that could be accrued, the project team collaborated with three utility partners (Duke Energy, Southern Company and Hawaiian Electric) to deliver improved probabilistic forecasts for each region and to model each region in case studies using advanced production cost modeling tools. Different methods to determine operating reserve requirements from probabilistic forecasts were developed, simulated, and tested across each region. The benefits of using these newly proposed methods varied by utility, but, in general, using probabilistic forecasts as well as historical data to set the reserve requirements seems to improve reliability related results, with less risk of reserve or supply shortfalls. The cost implications were not always straightforward; in some cases the new methods could show a reduction in expected operating costs, but often the increase in reserves associated with better risk mitigation using probabilistic forecasts could result in an increase in operating costs in the simulations. The SMP tool was developed to process probabilistic forecasts from their initial receipt through to scheduling decisions. This open-source tool consists of several modules for scenario development, reserve requirements calculation, and visualization. The SMP tool was demonstrated to a wide range of operators and stakeholders at all three utilities and further improved based on their feedback. The tool will be available on www.epri.com/optsun. The proposed probabilistic information-based reserve determination approaches have the potential to be implemented by different regions to ensure an economic and reliable power system operation on power systems integrating increasing levels of variable renewable resources. The innovative yet practical methods developed in this project demonstrated tangible benefits from using probabilistic forecasts beyond just study-based assessments to include three unique balancing areas. The demonstrated benefits across the multiple utility environments, are expected to provide system operators in all regions the confidence required and a platform to adopt the new forecasting and operating methods.

14 SOLAR ENERGY↗
DOE OSTI2013

Efficient and reliable 3D dose quality assurance for IMRT by combining independent dose calculations with measurements

Purpose: Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e., the hybrid-QA. The purpose of this study was to determine the reliability of the model-based QA and to evaluate time efficiency of the hybrid-QA method. Methods: Accuracy of the model-based QA was determined by comparison of COMPASS calculated dose with Monte Carlo calculations for heterogeneous media. In total, 330 intensity modulated radiation therapy (IMRT) treatment plans were evaluated based on the mean gamma index (GI) with criteria of 3%/3mm and classification of PASS (GI {<=} 0.4), EVAL (0.4 < GI > 0.6), and FAIL (GI {>=} 0.6). Agreement between model-based QA and measurement-based QA was determined for 48 treatment plans, and linac stability was verified for 15 months. Finally, time efficiency improvement of the hybrid-QA was quantified for four representative treatment plans. Results: COMPASS calculated dose was in agreement with Monte Carlo dose, with a maximum error of 3.2% in heterogeneous media with high density (2.4 g/cm{sup 3}). Hybrid-QA results for IMRT treatment plans showed an excellent PASS rate of 98% for all cases. Model-based QA was in agreement with measurement-based QA, as shown by a minimal difference in GI of 0.03 {+-} 0.08. Linac stability was high with an average GI of 0.28 {+-} 0.04. The hybrid-QA method resulted in a time efficiency improvement of 15 min per treatment plan QA compared to measurement-based QA. Conclusions: The hybrid-QA method is adequate for efficient and accurate 3D dose verification. It combines time efficiency of model-based QA with reliability of measurement-based QA and is suitable for implementation within any radiotherapy department.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Co-design optimization of combined heat and power-based microgrids

With the emergent need for clean and reliable energy resources, hybrid energy systems, such as the microgrid, are widely adopted in the United States. A microgrid can consist of various distributed energy resources, for instance, combined heat and power (CHP) systems. Here, the CHP module is a distributed cogeneration technology that produces electricity and recaptures heat generated as a by-product. It is an energy-efficient technology converting heat that would otherwise be wasted to valuable thermal energy. For an optimal system configuration, this study develops a novel co-design optimization framework for CHP-based cogeneration microgrids. The framework provides the stakeholder with a method to optimize investments and attain resilient operations. The proposed co-design framework has a mixed integer programming (MIP) model that outputs decisions for both plant designs and operating controls. The microgrid considered in this study contains six components: the CHP, boiler, heat recovery unit, thermal storage system, power storage system, and photovoltaic plant. After solving the MIP model, the optimal design parameters of each component can be found to minimize the total installation cost of all components in the microgrid. Furthermore, the online costs from energy production, operation, maintenance, machine startup, and disruption-induced unsatisfied loads are minimized by solving the optimal control decisions for operations. Case studies based on designing a CHP-based microgrid with empirical data are conducted. Moreover, we consider both nominal and disruptive operational scenarios to validate the performance of the proposed co-design framework in terms of a cost-effective, resilient system.

42 ENGINEERING↗
DOE OSTI2014

SU-E-T-471: Small Field Jaw/MLC Reference Data

Purpose: In recent years the need for small field data of MLCs has increased due to the use of intensity-modulated radiation (IMRT), but moreover the use of stereotactic body radiation (SBRT) has increased, which uses not simply small field sizes, but small jaw and field sizes together. Having reference data for these small fields that is reliable would be invaluable to the physics community. Our study has gathered these values and the data distributions from the Radiological Physics Center's (RPC) site visits between 1990 and the present. Methods: For all measurements, the RPC used a 25 × 25 × 25cm water phantom placed at 100cm SSD. All measurements were made with an Exradin A16 cylindrical ion chamber at an effective depth of 10 cm. A total of 42 Varian machine measurements were used to compose the data for a 6 MV beam and 5 TrueBeam 6 MV flattening filter free (FFF) beams were used for FFF data. Results: Jaw/MLC fields were measured for both 6 MV and 6 MF FFF beams with the jaws and MLCs both at the following field sizes: 6×6, 4×4, 3×3, and 2×2cm. Measurements were normalized to the 10×10 field readings (defined by the jaws and MLC). Spread in the data was minimal and demonstrates a high level of accuracy of acquired data. Conclusion: Small field Jaw/MLC reference data for Varian 6MV and 6 MV FFF beams has been analyzed and presented here, composed of the aggregation of numerous RPC site visits. Obtaining reliable small field data remains difficult, however the RPC has collected high fidelity small field Jaw/MLC data. The data are presented as a reference along with their distributions, in such a way that the physicist can act based upon their own desired agreement with the reference data.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Thermal Optimization of a Silicon Carbide, Half-Bridge Power Module

This project describes the modeling process to design the packaging and heat exchanger for a half-bridge wide-bandgap (WBG) power semiconductor module. The module uses two silicon carbide, metal-oxide-semiconductor field-effect transistor (MOSFET) devices per switch position that are soldered to an aluminum nitride, direct-bond copper (DBC) substrate. A baseplate cooling configuration (e.g., no thermal grease) is used along with a water-ethylene glycol, jet-impingement-style heat exchanger. The heat exchanger was designed to be fabricated using prototyping equipment from the National Renewable Energy Laboratory, complies with automotive standards (for minimal channel sizes, flow rates, and coolant), and considers reliability aspects (i.e., erosion/corrosion). Device-scale computational fluid dynamics (CFD) is used first to design the slot jet impingement cooling configuration and compute the effective heat transfer coefficient (HTC) of the concept. The computed HTCs are then used as boundary conditions for a finite element study to optimize the package geometry (e.g., device layout and baseplate thickness) to minimize thermal resistance and minimize temperature variation between the module's four devices. Finally, a fluid manifold is designed to generate the slot jets and cool the devices. Module-scale CFD predicts a relatively low junction-to-fluid thermal resistance of 16.7 mm2 K/W, a 1.4 degrees C temperature variation between devices, and a total pressure drop of 5,860 Pa (0.85 psi) for the design. The thermal resistance of the module design is about 67% lower than the 2015 BMW i3 power electronics/modules thermal resistance.

DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, G. C.↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗
DOE OSTI2021

Machine Learning for Improved Availability of the SNS Klystron High Voltage Converter Modulators

Beam availability has increased at the SNS, however, the targeted availability is greater than 95 %, while the SNS has failed to meet lower targets in the past. The HVCM used to power the linac klystrons have been one source of lost beam time and was chosen to explore using AI/ML techniques to improve reliability. Among the possibilities being explored are automating the tuning of HVCMs and predicting component failures such as capacitor aging, rectifier assemblies containing hundreds of diodes, and insulating oil degradation. The methodology pursued includes data cleaning, de-noising, post-analysis data labeling, and machine learning model development. We explore using Long Short-Term Memory and autoencoders for anomaly detection and prognostication used to schedule maintenance. We evaluate the use of model regularizers and constraints to improve the performance of the model and investigate methods to estimate the uncertainty of the models to provide a robust prediction with statistical interoperability. This paper describes the operational experience and known failures of the HVCMs and the proposed ML methodology and the preliminary results of training the AI/ML algorithms.

Pappas, Chris↗
DOE OSTI2025

Flat TBPS Integration Testing for the CMS Outer Tracker Upgrade

The upcoming High-Luminosity (HL) LHC will significantly increase luminosity, introducing more demanding operating conditions for the CMS detector. To meet these challenges, CMS is undergoing major upgrades, including a complete replacement of its tracking detector. This poster presents recent integration testing efforts conducted at Fermilab on the Flat Tracker Barrel with pixel-strip (PS) modules integration test stand, a subcomponent of the outer tracker located in the central barrel region. In this region, PS modules are mounted on structures that provide mechanical support and cooling, called planks. The testing focuses on validating the integrated system’s thermal and electrical performance. Results from these tests will be discussed, highlighting their importance for ensuring reliable tracker operation in the HL-LHC era.

Salazar Segovia, Itzelli [UC, Davis]↗
DOE OSTI2022

Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)

Abstract. Reliable soil biogeochemical modeling is a prerequisite for credible projections of climate change and associated ecosystem feedbacks. This recognition has called for frameworks that can support flexible and efficient development and application of new or alternative soil biogeochemical modules in Earth system models (ESMs). The the Biogeochemical Transport and Reaction model version 1 (BeTR-v1) code (i.e., CLM4-BeTR) is one such framework designed to accelerate the development and integration of new soil biogeochemistry formulations into ESMs and to analyze structural uncertainty in ESM simulations. With a generic reactive transport capability, BeTR-v1 can represent multiphase (e.g., gaseous, aqueous, and solid), multi-tracer (e.g., nitrate and organic carbon), and multi-organism (e.g., plants, bacteria, and fungi) dynamics. Here, we describe the new version, Biogeochemical Transport and Reaction model version 2 (BeTR-v2), which adopts more robust numerical solvers for multiphase diffusion and advection and coupling between biogeochemical reactions and improves code modularization over BeTR-v1. BeTR-v2 better supports different mathematical formulations in a hierarchical manner by allowing the resultant model be run for a single topsoil layer or a vertically resolved soil column, and it allows the model to be fully coupled with the land component of the Energy Exascale Earth System Model (E3SM). We demonstrate the capability of BeTR-v2 with benchmark cases and example soil biogeochemical (BGC) implementations. By taking advantage of BeTR-v2's generic structure integrated in E3SM, we then found that calibration could not resolve biases introduced by different numerical coupling strategies of plant–soil biogeochemistry. These results highlight the importance of numerically robust implementation of soil biogeochemistry and coupling with hydrology, thermal dynamics, and plants – capabilities that the open-source BeTR-v2 provides. We contend that Earth system models should strive to minimize this uncertainty by applying better numerical solvers.

58 GEOSCIENCES↗
DOE OSTI2014

Recent Photovoltaic Performance Data in the USA (Presentation)

This paper presents performance data from nearly 50,000 Photovoltaic systems totaling 1.7 Gigawatts installed capacity in the USA from 2009 to 2012. 90% of the systems performed to within 10% or better of expected performance. Only 2-4% of the data indicate issues significantly affecting the system performance. Special causes of underperformance and their impacts are delineated by reliability category. Delays and interconnections dominate project-related issues particularly in the first year, but total less than 0.5% of all systems. Hardware-related issues are dominated by inverter problems totaling less than 0.4% and underperforming modules to less than 0.1%.

14 SOLAR ENERGY↗
DOE OSTI2021

Probing the electronic properties of the electrified silicon/water interface by combining simulations and experiments.

Silicon (Si) is broadly used in electrochemical and photoelectrochemical devices, where the capacitive and Faradaic reactions at the Si/water interfaces are critical for signal transduction or noise generation. However, probing the electrified Si/water interface at the microscopic level remains a challenging task. Here we focus on hydrogenated Si surfaces in contact with water, relevant to transient electronics and photoelectrochemical modulation of biological cells and tissues. We show that by carrying out first principles molecular dynamics simulations of the Si(100)/water interface in the presence of an electric field we can realistically correlate the computed flat-band potential and tunneling current images at the interface with experimentally measured capacitive and Faradaic currents. Specifically, we validate our simulations in the presence of bias by performing pulsed chronoamperometry measurements on Si wafers in solution. Consistent with prior experiments, our measurements and simulations indicate the presence of voltage-dependent capacitive currents at the interface. We also find that Faradaic currents are weakly dependent on the applied bias, which we relate to surface defects present in newly prepared samples.

Ye, Zifan↗
DOE OSTI2021

Failure Analysis of a New Polyamide-Based Fluoropolymer-Free Backsheet After Combined-Accelerated Stress Testing

The viability of novel coextruded, fluoropolymer-free backsheets for photovoltaic (PV) modules has been questioned as a result of a large number of early-life backsheet failures in PV installations containing one of the earliest co-extruded polyamide (PA)-based backsheet to reach the market, “AAA.” New PV reliability testing protocols have been recently developed and applied to backsheets to reproduce failures observed in the field and evaluate the durability of novel backsheet materials and designs prior to commercialization. A new co-extruded PA-based backsheet was tested using combined-accelerated stress testing (C-AST) and demonstrated a greater lifetime than AAA, and some other fluoropolymer-based backsheets such as polyvinylidene fluoride. The improved PA-based backsheet also eventually failed by through-thickness cracking. Using surface and bulk material characterization techniques, we performed a comprehensive study of material properties before and after the stress testing. Aging of the backsheet resulted in an increase of surface roughness by erosion of the outer PA layer. However the failure is more likely related to an increase in crystallinity of the polyolefin core layer reducing the backsheet tearing energy. The analysis can ultimately inform on the specific weaknesses of the materials so that the manufacturer can improve the backsheet design to extend its lifetime.

14 SOLAR ENERGY↗
DOE OSTI2021

Cracked Solar Cell Performance Depends on Module Temperature

When cells in a crystalline silicon photovoltaic module crack, packaging materials hold the fragments together. Changes in module temperature cause cell fragments to move, allowing cracked metallization to lose and regain contact. We intentionally cracked cells in commercial PV modules and characterized the modules’ temperature-dependent electroluminescence (EL) response. Here we show that (1) metallization makes contact across cracks in a way that is temperature dependent and (2) this contact is not a function of temperature, but is hysteretic. We expect that any electro-optical characterization made at a single temperature will be misleading as to the effects of cracked cells at different temperatures. And we expect that a single temperature sweep cannot fully characterize the temperature dependence of electro-optical performance of modules with cracked cells.

crack↗
DOE OSTI2024

Cholla-MHD: An Exascale-capable Magnetohydrodynamic Extension to the Cholla Astrophysical Simulation Code

Abstract We present an extension of the massively parallel, GPU native, astrophysical hydrodynamics code Cholla to magnetohydrodynamics (MHD). Cholla solves the ideal MHD equations in their Eulerian form on a static Cartesian mesh utilizing the Van Leer + constrained transport integrator, the HLLD Riemann solver, and reconstruction methods at second and third order. Cholla’s MHD module can perform ≈260 million cell updates per GPU-second on an NVIDIA A100 while using the HLLD Riemann solver and second order reconstruction. The inherently parallel nature of GPUs combined with increased memory in new hardware allows Cholla’s MHD module to perform simulations with resolutions ∼500 3 cells on a single high-end GPU (e.g., an NVIDIA A100 with 80 GB of memory). We employ GPU direct Message Passing Interface to attain excellent weak scaling on the exascale supercomputer Frontier, while using 74,088 GPUs and simulating a total grid size of over 7.2 trillion cells. A suite of test problems highlights the accuracy of Cholla’s MHD module and demonstrates that zero magnetic divergence in solutions is maintained to round off error. We also present new testing and CI tools using GoogleTest, GitHub Actions, and Jenkins that have made development more robust and accurate and ensure reliability in the future.

Astronomy & Astrophysics↗