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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Changes in Cirrus Cloudiness and their Relationship to Contrails

Condensation trails, or contrails, formed in the wake of high-altitude aircraft have long been suspected of causing the formation of additional cirrus cloud cover. More cirrus is possible because 10 - 20% of the atmosphere at typical commercial flight altitudes is clear but ice-saturated. Since they can affect the radiation budget like natural cirrus clouds of equivalent optical depth and microphysical properties, contrail -generated cirrus clouds are another potential source of anthropogenic influence on climate. Initial estimates of contrail radiative forcing (CRF) were based on linear contrail coverage and optical depths derived from a limited number of satellite observations. Assuming that such estimates are accurate, they can be considered as the minimum possible CRF because contrails often develop into cirrus clouds unrecognizable as contrails. These anthropogenic cirrus are not likely to be identified as contrails from satellites and would, therefore, not contribute to estimates of contrail coverage. The mean lifetime and coverage of spreading contrails relative to linear contrails are needed to fully assess the climatic effect of contrails, but are difficult to measure directly. However, the maximum possible impact can be estimated using the relative trends in cirrus coverage over regions with and without air traffic. In this paper, the upper bound of CRF is derived by first computing the change in cirrus coverage over areas with heavy air traffic relative to that over the remainder of the globe assuming that the difference between the two trends is due solely to contrails. This difference is normalized to the corresponding linear contrail coverage for the same regions to obtain an average spreading factor. The maximum contrail-cirrus coverage, estimated as the product of the spreading factor and the linear contrail coverage, is then used in the radiative model to estimate the maximum potential CRF for current air traffic.

Minnis, Patrick↗
DOE OSTI2020

The energy footprint of automotive electronic sensors

We discuss how Information and communication technologies (ICT) have emerged as one of the leading technologies to reduce global emissions, particularly in the mobility sector. Automotive electronics, such as sensors/actuators and microcontrollers (commonly known as electronic control units (ECU) which control one or more of the electrical systems or subsystems in a vehicle), play a key role in ICT. Sensors/actuators are key in electronic ICT devices, starting with the data collection and data communication with the internet. The latest two big trends of electrification and automation in vehicles, are projected to increase the use of worldwide automotive sensors from 7.5 billion units in 2017 to 11.0 billion units by the year 2024. A representative state-of-the art automotive sensor system, (i.e., an ultrasonic backup system), including the ECUs controlling the vehicle electrical systems/subsystems, has been considered to estimate the energy footprint in terms of manufacturing and operational energy of global automotive sensors use. A widely used life cycle energy assessment method (i.e., cumulative energy demand) was used as both direct and indirect (including the extraction, manufacturing, and disposal of the raw and auxiliary materials) energy use can be considered for the energy footprint estimation. The embodied manufacturing energy impacts of the system was estimated to be 559 MJ/system, compared to the 417 MJ/system for lifetime system power and additional gasoline use. The share of purchased energy to the embodied energy where the upstream energy isn't included in the former case, is less than 10% and ~ 85% for the component manufacturing and vehicle operation energy uses, respectively. As the purpose of this ultrasonic backup system is to prevent rear crashes, an estimated 1.0 MJ/system is avoided from reduced lifetime vehicular repairs (from an estimated 11% chance of requiring a rear bumper replacement). While all of this is small compared to the overall automotive manufacturing and use energy, the 11 billion automotive sensors expected to be produced in 2024 could require 1540 PJ for manufacturing and those sensors would require an additional 780–1150 PJ for lifetime energy use.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1988

Computed potential energy surfaces for chemical reactions

The minimum energy path for the addition of a hydrogen atom to N2 is characterized in CASSCF/CCI calculations using the (4s3p2d1f/3s2p1d) basis set, with additional single point calculations at the stationary points of the potential energy surface using the (5s4p3d2f/4s3p2d) basis set. These calculations represent the most extensive set of ab initio calculations completed to date, yielding a zero point corrected barrier for HN2 dissociation of approx. 8.5 kcal mol/1. The lifetime of the HN2 species is estimated from the calculated geometries and energetics using both conventional Transition State Theory and a method which utilizes an Eckart barrier to compute one dimensional quantum mechanical tunneling effects. It is concluded that the lifetime of the HN2 species is very short, greatly limiting its role in both termolecular recombination reactions and combustion processes.

Walch, Stephen P.↗
DOE OSTI2021

Impact of duration and missing data on the long-term photovoltaic degradation rate estimation

Accurate quantification of photovoltaic (PV) system degradation rate (R D ) is essential for lifetime yield predictions. Although R D is a critical parameter, its estimation lacks a standardized methodology that can be applied on outdoor field data. The purpose of this paper is to investigate the impact of time period duration and missing data on R D by analyzing the performance of different techniques applied to synthetic PV system data at different linear R D patterns and known noise conditions. The analysis includes the application of different techniques to a 10-year synthetic dataset of a crystalline Silicon PV system, with emulated degradation levels and imputed missing data. Here, the analysis demonstrated that the accuracy of ordinary least squares (OLS), year-on-year (YOY), autoregressive integrated moving average (ARIMA) and robust principal component analysis (RPCA) techniques is affected by the evaluation duration with all techniques converging to lower R D deviations over the 10-year evaluation, apart from RPCA at high degradation levels. Moreover, the estimated R D is strongly affected by the amount of missing data. Filtering out the corrupted data yielded more accurate R D results for all techniques. It is proven that the application of a change-point detection stage is necessary and guidelines for accurate R D estimation are provided.

14 SOLAR ENERGY↗
DOE OSTI2023

Degradation of Insulating Glass Units: Thermal Performance, Measurements and Energy Impacts

Insulating glass unit (IGU) degradation has been studied extensively. However, there is limited understanding of how present durability evaluation standards relate to product lifetime. Furthermore, there is debate on how to quantify performance of installed windows over time to better understand degradation processes. More knowledge on these topics is required to link durability evaluation to product lifetime projections based on energy performance. Energy models provide helpful estimations of total annual building energy consumption. However, most models are based on “as installed” performance of envelope components and fail to account for performance degradation. This can lead to an underestimation of building lifetime energy consumption. A better understanding of the relationship between durability and energy performance can inform integration of degradation dynamics into energy modeling software. This will improve lifetime building energy consumption estimations as well as inform appropriate retrofit strategies and timing. This paper reviews current durability literature, various standards for window performance ratings and weathering methods, existing in situ IGU energy performance measurement techniques, and whole-building energy effects. The challenges and disparities among various studies are analyzed and discussed. The authors hope that further work in this area will lead to the development of improved in situ test methods to assess IGU degradation in the field and link this knowledge to improved energy performance modeling approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1989

Theoretical characterization of the minimum energy path for hydrogen atom addition to N2 - Implications for the unimolecular lifetime of HN2

Results are reported from CASSCF externally contracted CI ab initio computations of the minimum-energy path for the addition of H to N2. The theoretical basis and numerical implementation of the computations are outlined, and the results are presented in extensive tables and graphs and characterized in detail. The zero-point-corrected barrier for HN2 dissociation is estimated as 8.5 kcal/mol, and the lifetime of the lowest-lying quasi-bound vibrational state of HN2 is found to be between 88 psec and 5.8 nsec (making experimental observation of this species very difficult).

Walch, Stephen P.↗
NASA NTRS1984

The atmospheric lifetime of methylchloroform (CH3CCl3)

The lifetime of atmospheric methylchloroform (CH3CCl3) is estimated to be about 6 (+ or - 1.5) years based on extensive measurements taken over the past seven years at remote locations of the world, ranging from inside the Arctic Circle to the South Pole. The average level of tropospheric hydroxyl radicals (OH) deduced from the lifetime of CH3CCl3 is about 8 x 10 to the 5th molecules/cu cm, but this value is uncertain by up to + or - 75 percent.

Khalil, M. A. K.↗
NASA NTRS1987

The area-time-integral technique to estimate convective rain volumes over areas applied to satellite data - A preliminary investigation

The use of the area-time-integral (ATI) technique, based only on satellite data, to estimate convective rain volume over a moving target is examined. The technique is based on the correlation between the radar echo area coverage integrated over the lifetime of the storm and the radar estimated rain volume. The processing of the GOES and radar data collected in 1981 is described. The radar and satellite parameters for six convective clusters from storm events occurring on June 12 and July 2, 1981 are analyzed and compared in terms of time steps and cluster lifetimes. Rain volume is calculated by first using the regression analysis to generate the regression equation used to obtain the ATI; the ATI versus rain volume relation is then employed to compute rain volume. The data reveal that the ATI technique using satellite data is applicable to the calculation of rain volume.

Doneaud, Andre A.↗
DOE OSTI2022

Thermal Stress Reduction in Power Switching Devices Using Distributed Loss PWM Concept for Current Source Inverters

A new modulation scheme is proposed for current source inverters (CSIs) that reduces the variation and peak junction temperature in the CSIs' power devices. The distributed loss pulse-width modulation (DLM) concept is introduced and applied to traditional space vector modulation methods to develop modified modulation schemes that reduce the thermal stress on power devices. The device junction temperatures resulting from conventional and DLM schemes are compared. Simulation and experimental results confirm that the proposed DLM concept reduces thermal stress on the devices while maintaining the same high output current waveform quality compared to traditional CSI modulation schemes. The CSI power device lifetime (i.e., the number of cycles to failure) are estimated using the simulation and experimental results. The proposed DLM significantly increases the device lifetime (by 5 to 6 times) by reducing the junction temperature variation compared to the conventional modulations.

42 ENGINEERING↗
DOE OSTI2024

RESIN: Responsible Innovation for Highly Recyclable Plastics - TASK 4: Risk Assessment Framework

This report covers the entirety of Task 4, but its main purpose is to deliver milestones ML4.4 and ML4.5, the last two SOPO milestones under Task 4. ML4.4 reports on the compatibility of polymer properties that affect both environmental performance and functional performance and the tradeoffs involved in turning these properties to the benefit of each. ML4.5 presents a complete set of information on the critical properties of benign target products, where benign products are defined as those with the shortest environmental lifetime which meet performance requirements. To support and provide context to the discussions of ML4.4 and ML4.5 and to provide a complete picture of Task 4, milestones 4.1-4.3 are briefly summarized at the beginning of the report. The discussion of ML4.4 introduces the notion of polymer persistence as a proxy for environmental risk. It then discusses the development and comparison of two machine leaning models explored for estimating polymer degradation rates, a random forest (RF) classifier and an RF regressor. Given the advantage of continuous outputs rather than simple classes, the RF regressor was incorporated in the Excel risk calculator, which to this point could implement the objectives of subtasks 4.1-4.3, estimating polymer release and redistribution. The ML4.4 discussion then addresses the effect of each of the three polymer features used by the RF regressor on polymer functional performance. These features are number molecular weight (Mn), glass transition temperature (T g ) and heat of fusion (H fus ). The discussion of ML4.5 reviews the conceptual framework of the risk model, which served as the foundation for developing the Excel risk calculator and describes the use of, and assumptions within, the calculator. Appendix A is further provided as a user’s guide for the calculator. To demonstrate how the calculator is intended to be used by developers in the design of low-risk polymers, an analysis of 27 hypothetical polymers defined by varying values for the three polymer features used by the RF regressor is presented. The range of parameter values selected produces estimates of polymer degradation rates and lifetimes that may be typical of various consumer products made from polyurethane polymers and shows how changes in polymer features affect lifetimes. The demonstration also predicts the final distribution of released polymer materials in environmental compartments as a function of consumer product mix and assumed leakage rates of end-of-life processes. Lastly, this report summarizes the achievement of Task 4 goals from original conception to final delivery and discusses how and to what degree to which each subtask goal was achieved.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1987

Atmospheric trends in methylchloroform and the global average for the hydroxyl radical

ALE-GAGE (Atmospheric Lifetime Experiment-Global Atmospheric Gases Experiment) data obtained over the seven-year period from July 1978 to June 1985 are presented and interpreted. The data, combined with knowledge of industrial emissions, are used in an optimal estimation inversion scheme to deduce a globally average methylchloroform atmospheric lifetime of 6.3(+ 1.2, - 0.9) years (1 sigma uncertainty) and a globally averaged tropospheric hydroxyl radical concentration of (7.7 + or - 1.4) x 10 to the 5th radicals/cu cm (1 sigma uncertainty). These results provide the most accurate estimates yet of the trends and lifetime of methylchloroform and of the global average for tropospheric hydroxyl radical levels.

Prinn, R.↗
DOE OSTI2022

Machine-Learning Assisted Identification of Accurate Battery Lifetime Models with Uncertainty

Reduced-order battery lifetime models, which consist of algebraic expressions for various aging modes, are widely utilized for extrapolating degradation trends from accelerated aging tests to real-world aging scenarios. Identifying models with high accuracy and low uncertainty is crucial for ensuring that model extrapolations are believable, however, it is difficult to compose expressions that accurately predict multivariate data trends; a review of cycling degradation models from literature reveals a wide variety of functional relationships. Here, a machine-learning assisted model identification method is utilized to fit degradation in a stand-out LFP-Gr aging data set, with uncertainty quantified by bootstrap resampling. The model identified in this work results in approximately half the mean absolute error of a human expert model. Models are validated by converting to a state-equation form and comparing predictions against cells aging under varying loads. Parameter uncertainty is carried forward into an energy storage system simulation to estimate the impact of aging model uncertainty on system lifetime. The new model identification method used here reduces life-prediction uncertainty by more than a factor of three (86% ± 5% relative capacity at 10 years for human-expert model, 88.5% ± 1.5% for machine-learning assisted model), empowering more confident estimates of energy storage system lifetime.

25 ENERGY STORAGE↗
DOE OSTI2023

Battery Charge Curve Prediction via Feature Extraction and Supervised Machine Learning

Real-time onboard state monitoring and estimation of a battery over its lifetime is indispensable for the safe and durable operation of battery-powered devices. In this study, a methodology to predict the entire constant-current cycling curve with limited input information that can be collected in a short period of time is developed. A total of 10 066 charge curves of LiNiO 2 -based batteries at a constant C-rate are collected. With the combination of a feature extraction step and a multiple linear regression step, the method can accurately predict an entire battery charge curve with an error of < 2% using only 10% of the charge curve as the input information. The method is further validated across other battery chemistries (LiCoO 2 -based) using open-access datasets. The prediction error of the charge curves for the LiCoO 2 -based battery is around 2% with only 5% of the charge curve as the input information, indicating the generalization of the developed methodology for predicting battery cycling curves. The developed method paves the way for fast onboard health status monitoring and estimation for batteries during practical applications.

25 ENERGY STORAGE↗
DOE OSTI2023

From Hydrometeor Size Distribution Measurements to Projections of Wind Turbine Blade Leading-Edge Erosion

Wind turbine blade leading-edge erosion (LEE) is a cause of increased operation and maintenance costs and decreased annual energy production. Thus, detailed, site-specific quantification of likely erosion conditions are critically needed to inform wind plant owner/operator decisions regarding mitigation strategies. Estimating the damage potential at a wind plant site requires accurate measurement of precipitation intensity, phase, droplet size distributions, wind speeds and their joint statistics. The current work quantifies the effect of disdrometer type on the characterization of LEE potential at a site in the US Southern Great Plains. using observations from three co-located disdrometers (an optical, an impact and a video disdrometer), along with hub-height wind-speed observations from a Doppler lidar and two LEE models: a kinetic energy model and the Springer model. Estimates of total kinetic energy of hydrometeor impacts over the four-year study period vary by as much as 38%, and coating lifetime derived from accumulated distance-to-failure estimates from the Springer model differ by an even greater amount, depending on disdrometer type. Damage potential at this site is concentrated in time, with 50% of impact kinetic energy occurring in 6–12 h per year, depending on which set of disdrometer observations is used. Rotor-speed curtailment during the most erosive 0.1–0.2% of 10 min periods is found to increase blade lifetimes and lead to the lowest levelized cost of energy.

17 WIND ENERGY↗
NASA NTRS1972

Electron and proton flux models for Jupiter's radiation belts

Estimates of the energetic particle distribution in Jupiter's radiation belts are presented and are compared with previous estimates. Mathematical expressions are developed for the equatorial electron and proton fluxes, shielded electron and proton dose rates, and radiation lifetimes of electronic circuits. It is calculated that a 1 g/sq cm aluminum shield will screen out all protons of energy less than 27.5 MeV, and a 2 g/sq cm shield will screen out protons less than 40.6 MeV. The radiation lifetimes are based on a maximum permissible dose value of 10 million rads, a value 1/2 to 1/3 of the flux at which electronic circuits begin to fail. Estimated increases in lifetimes by using a 3 x 50 orbit instead of a 3 x 3 orbit, and going from 1 to 2 g/sq cm are given.

Klopp, D. A.↗
DOE OSTI2023

Comparing Parallel Plastic‐to‐X Pathways and Their Role in a Circular Economy for PET Bottles

Abstract The United States generates the most plastic waste of any country and is a top contributor to global plastic pollution. Multiple end‐of‐life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different lifetimes and utilities. Herein, they present a material flow model equipped with consequential life cycle assessment, cost analysis, and a plastic circularity indicator that considers product quality and lifetime. The model is used to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) bottle mechanical downcycling to lower‐quality resin, closed‐loop glycolysis to food‐grade PET, upcycling to glass fiber‐reinforced plastic, and conversion to non‐plastic products (electricity, oil) on a United States economy‐wide basis for the year 2020. A brute force algorithm suggests that a combination of 68% glycolysis, 11% mechanical recycling, 6% upcycling, 9% landfilling, and 5% incineration can minimize the cost and GHG emissions and maximize the circularity of the current PET economy. However, uncertainty around transportation distances, materials recovery facility efficiencies, and recycling yields can result in different “optimal” pathway mixes. This flexible framework enables informed decision‐making to move toward a cost‐ and environment‐conscious circular economy for plastic.

09 BIOMASS FUELS↗