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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Polarization Type Potential Induced Degradation under Positive Bias in a Commercial PERC Module: Preprint

Potential induced degradation of the polarization type (PID-p) can reduce module performance in a relatively short period of time. PID-p can occur at both voltage polarities, but most studies are focused on degradation under a negative bias. This paper uses commercial bifacial passivated emitter and rear contact (PERC) cells within a monofacial glass-backsheet module construction to evaluate the impact of PID-p under a positive bias on the front side. Using the aluminum-foil (Al-foil) method, the module was stressed for PID in an environmental chamber. After the stress, the maximum power (Pmax) showed a decline of 3.1% at 1000 W/m2 and 6.2% at 200 W/m2. Recovery under light was also investigated. Complete recovery was observed at high irradiance, while a partial recovery was seen at lower irradiance. The outcomes of this study can help in understanding PID-p degradation under a positive bias and its recovery under the light.

PERC↗
DOE OSTI2021

An overview of wind-energy-production prediction bias, losses, and uncertainties

Abstract. The financing of a wind farm directly relates to the preconstruction energy yield assessments which estimate the annual energy production for the farm. The accuracy and the precision of the preconstruction energy estimates can dictate the profitability of the wind project. Historically, the wind industry tended to overpredict the annual energy production of wind farms. Experts have been dedicated to eliminating such prediction errors in the past decade, and recently the reported average energy prediction bias is declining. Herein, we present a literature review of the energy yield assessment errors across the global wind energy industry. We identify a long-term trend of reduction in the overprediction bias, whereas the uncertainty associated with the prediction error is prominent. We also summarize the recent advancements of the wind resource assessment process that justify the bias reduction, including improvements in modeling and measurement techniques. Additionally, because the energy losses and uncertainties substantially influence the prediction error, we document and examine the estimated and observed loss and uncertainty values from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 wind resource assessment standard. From our findings, we highlight opportunities for the industry to move forward, such as the validation and reduction of prediction uncertainty and the prevention of energy losses caused by wake effect and environmental events. Overall, this study provides a summary of how the wind energy industry has been quantifying and reducing prediction errors, energy losses, and production uncertainties. Finally, for this work to be as reproducible as possible, we include all of the data used in the analysis in appendices to the article.

17 WIND ENERGY↗
DOE OSTI2023

Reverse-Bias Resilience of Monolithic Perovskite/Silicon Tandem Solar Cells

Metal halide perovskites have rapidly enabled a range of high-performance photovoltaic technologies. However, catastrophic failure under reverse voltage bias poses a roadblock for their commercialization. In this work, we conduct a series of stress tests to compare the reverse-bias stability of perovskite single-junction, silicon single-junction, and monolithic perovskite/silicon tandem solar cells. We demonstrate that the tested perovskite/silicon tandem devices are considerably more resilient against reverse bias compared with perovskite single-junction devices. The origin of such improved stability stems from the low reverse-bias diode current of the silicon subcell. This translates to dropping most of the voltage over the silicon subcell, where such a favorable voltage distribution protects the perovskite subcell from reverse-bias-induced degradation. These results highlight that, compared with other perovskite technologies, monolithic perovskite/silicon tandems are at a higher technology readiness level in terms of tackling the reverse bias and partial shading challenges, which is a considerable advantage toward commercialization.

halide perovskite↗
DOE OSTI2024

Barrier reinforcement for enhanced perovskite solar cell stability under reverse bias

Stability of perovskite solar cells (PSCs) under light, heat, humidity and their combinations have been notably improved recently. However, PSCs have poor reverse-bias stability that limits their real-world application. Here we report a systematic study on the degradation mechanisms of p-i-n structure PSCs under reverse bias. The oxidation of iodide by injected holes at the cathode side initialize the reverse-bias-induced degradation, then the generated neutral iodine oxidizes metal electrode such as copper, followed by drift of Cu+ into perovskites and its reduction by injected electrons, resulting in localized metallic filaments and thus device breakdown. A reinforced barrier with combined lithium fluoride, tin oxide and indium tin oxide at the cathode side reduces device dark current and avoids the corrosion of Cu0. It dramatically increases breakdown voltage to above -20 V and improved the T90 lifetime of PSCs to ~1,000 h under -1.6 V. The modified minimodule also maintained over 90% of its initial performance after 720 h of shadow tests.

degradation mechanisms↗
DOE OSTI2022

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Cloud Influence on ERA5 and AMPS Surface Downwelling Longwave Radiation Biases in West Antarctica

The surface downwelling longwave radiation component (LW?) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW? signal measured at the surface. In this study, we examine the LW? model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 reanalysis model relative to observations from the AWARE campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear sky conditions, ice cloud occurrences, and liquid-bearing cloud layer (LBCL) occurrences. The analysis results show a tendency (in both models at each site) to underestimate the LW? during clear sky conditions, high error variability (standard deviations > 20 W/m2) during any type of cloud occurrence, and negative LW? biases when LBCLs are observed (bias magnitudes > 15 W/m2 in tenuous LBCL cases; > 43 W/m2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid water-deficient atmosphere responsible for the identified LW? biases in both models is the result of excessive ice formation and growth, which could stem from model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.

Silber, Israel↗
DOE OSTI2018

Biasing Smarter, Not Harder, by Partitioning Collective Variables into Families in Parallel Bias Metadynamics

Molecular simulations of systems with multiple copies of identical atoms or molecules may require the biasing of numerous, degenerate collective variables (CVs) to accelerate sampling. Recently, a variation of metadynamics (MetaD) named parallel bias metadynamics (PBMetaD) has been shown to make biasing of many CVs more tractable. We extended the PBMetaD scheme so that it partitions degenerate CVs into families that share the same bias potential, consequently expediting convergence of the free-energy landscape. We tested our method, named parallel bias metadynamics with partitioned families, on 3, 21, and 78 CV systems and obtained an approximately proportional increase in convergence speed compared to standard PBMetaD.

Prakash, Arushi↗
DOE OSTI2018

Highly Contrasting Static Charging and Bias Stress Effects in Pentacene Transistors with Polystyrene Heterostructures Incorporating Oxidizable N , N '-Bis(4-methoxyphenyl)aniline Side Chains as Gate Dielectrics

Charge storage and trapping properties of polymer dielectrics govern the charge densities of adjacent semiconductors and greatly influence the on-off switching voltage (threshold voltage, V th ) of organic field-effect transistors (OFETs) when the polymers are used as gate insulators. Intentional charging of polymer dielectrics in OFETs can change V th and affect the bias stress. We describe a chemical design and fabrication protocol to construct multilayer-stack dielectrics for pentacene-based OFETs using different polystyrene (PS)-based polymers in each layer, with oxidizable N,N-bis(4-methoxyphenyl)anilino (TPAOMe)-substituted styrene copolymers in arbitrary vertical positions in the stacks. Thermal, byproduct-free crosslinking of benzocyclobutene subunits provides integrity to the multilayer structure by preventing dissolution of the previous deposited layer. Neutron reflectivity data verified the multilayer morphology. We compared the Vth shift before and after charging the stacks by application of ±100V across 0.5-1 µm total film thicknesses. Bias stress was the dominant effect in bilayer devices with a TPAOMe layer in contact with the pentacene, indicated by the direction of V th shift associated with either polarity of external electric field. In structures with no TPAOMe subunit in contact with the pentacene, when charging with -100V on top of the source and drain electrodes, electron injection from pentacene to dielectric was the major charging mechanism, again consistent with the bias stress direction. When charging with +100V, bilayer devices without TPAOMe showed little change in V th , suggesting there was no bias stress effect or charge injection in these devices for this charging polarity. For the bilayer devices with the TPAOMe layer in the bottom, and the trilayer devices with TPOMe in the middle, when +100V was applied, the V th shifts were opposite those expected from bias stress. Dipole formation or partial ionization of chargeable groups at the interface between the dielectric layers are likely polarization mechanisms in these cases. A simple analytical model supports the plausibility of these mechanisms. This work provides examples of both stabilization and shifting of V th , and therefore controlling charge carrier density, in semiconductors overlying the dielectric multilayers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1974

Fore and aft elastic response characteristics of 34 x 9.9, type 7, 14 ply-rating aircraft tires of bias-ply, bias-belted, and radial-belted design

An investigation was conducted to determine the fore-and-aft elastic response characteristics of 34 x 9.9, type VII, 14 ply-rating aircraft tires of bias-ply, bias-belted, and radial-belted design. The investigation consisted of static and rolling tests on dry concrete pavements at the Langley aircraft landing loads and traction facility; statistical techniques which related the measured tire elastic characteristics to variations in the vertical load, inflation pressure, braking force and/or tire vertical deflection; and a semiempirical analysis which related the tire elastic behavior to measured wheel slippage during steady-state braking. The bias-belted tire developed the largest spring constant value for most loading conditions; the radial-belted tire, the smallest. The elastic response of the tire free periphery to static braking included both tread stretch and carcass torsional wind-up about the axle for the bias-ply and bias-belted tires and carcass wind-up alone for the radial-belted tire.

Tanner, J. A.↗
NASA NTRS2011

Study of the Dependence on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter

At SRON we are studying the performance of a Goddard Space Flight Center single pixel TES microcalorimeter operated in the AC bias configuration. For x-ray photons at 6keV the AC biased pixel shows a best energy resolution of 3.7eV, which is about a factor of 2 worse than the energy resolution observed in identical DC-biased pixels. To better understand the reasons of this discrepancy, we investigated the detector performance as a function of temperature, bias working point and applied magnetic field. A strong periodic dependence of the detector noise on the TES AC bias voltage is measured. We discuss the results in the framework of the recent weak-link behaviour observed inTES microcalorimeters.

Bandler, Simon↗
DOE OSTI2022

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Epperson, David L.↗
NASA NTRS2012

Study of the Dependency on Magnetic Field and Bias Voltage of an AC-Biased TES Microcalorimeter

At SRON we are studying the performance of a Goddard Space Flight Center single pixel TES microcalorimeter operated in an AC bias configuration. For x-ray photons at 6 keV the pixel shows an x-ray energy resolution Delta E(sub FWHM) = 3.7 eV, which is about a factor 2 worse than the energy resolution observed in an identical DC-biased pixel. In order to better understand the reasons for this discrepancy we characterized the detector as a function of temperature, bias working point and applied perpendicular magnetic field. A strong periodic dependency of the detector noise on the TES AC bias voltage is measured. We discuss the results in the framework of the recently observed weak-link behaviour of a TES microcalorimeter.

Gottardi, L.↗
DOE OSTI2017

Simulation–Extrapolation for Bias Correction with Exposure Uncertainty in Radiation Risk Analysis Utilizing Grouped Data

Summary In observational epidemiological studies, the exposure that is received by an individual often cannot be precisely observed, resulting in measurement error, and a common approach to dealing with measurement error is regression calibration (RC). Use of RC, which requires assumptions about the distribution of unknown error-free (true) variables, leads to concern about the possibility of bias due to misspecification of that distribution. The simulation–extrapolation (SIMEX) method, in contrast, does not require a distributional assumption. However, analyses of large cohorts may be performed by using grouped or person-year data, and application of SIMEX to grouped data is not straightforward, particularly when there is a mixture of classical and Berkson measurement errors. We compared RC and SIMEX with grouped data analyses to assess robustness of the RC method to misspecification of the true dose distribution. We also applied SIMEX assuming mixtures of classical and Berkson errors and compared the results with those obtained by using RC for classical error only. SIMEX had less bias than RC and performed well regardless of the true dose distribution, whereas RC based on a misspecified true dose distribution showed greater bias than when based on the correctly specified true dose distribution.

Misumi, Munechika↗
NASA NTRS1973

Fore and aft elastic response characteristics of size 34x9.9, type 7, 14 ply-rated aircraft tires of bias ply, bias belted, and radial belted design

An investigation was conducted to determine the fore-and-aft elastic response characteristics of aircraft tires of bias ply, bias-belted, and radial-belted design. The investigation consisted of: (1)static and rolling tests, (2)a statistical analysis which related the measured tire elastic characteristics to variations in the vertical load, inflation pressure, braking force and/or tire vertical deflection, and (3) a semi-empirical analysis which related the tire elastic behavior to measured wheel slippage during a steady-state braking. The results of this investigation indicate that the bias-belted tire has the largest spring constant value for most loading conditions and the radial-belted tire has the smallest spring constant value.

Tanner, J. A.↗
DOE OSTI2025

Pentaerythritol structure-directing agents bias aluminum siting in MFI zeolites to increase para -xylene selectivity during toluene methylation

MFI zeolites contain ten-membered ring channels (∼0.55 nm diameter) that intersect to form larger voids (∼0.70 nm diameter). The distribution of framework Al sites dictates the void environments that confine active H + sites. MFI synthesized with pentaerythritol (PET) and Na + as structure-directing agents are interrogated using kinetically controlled toluene methylation rates and xylene isomer selectivities. High para-xylene selectivity and low toluene methylation rates indicate that MFI-PET samples contain H + sites predominantly in smaller channels. As-synthesized samples contain more framework Al than Na + , indicating that some charge compensation is provided by protonated PET-solvent complexes that bias Al siting towards these smaller channels.

36 MATERIALS SCIENCE↗