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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (≤1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Li, Xuanli↗
NASA NTRS2014

Assimilation of Dual-Polarimetric Radar Observations with WRF GSI

Dual-polarimetric (dual-pol) radar typically transmits both horizontally and vertically polarized radio wave pulses. From the two different reflected power returns, more accurate estimate of liquid and solid cloud and precipitation can be provided. The upgrade of the traditional NWS WSR-88D radar to include dual-pol capabilities will soon be completed for the entire NEXRAD network. Therefore, the use of dual-pol radar network will have a broad impact in both research and operational communities. The assimilation of dual-pol radar data is especially challenging as few guidelines have been provided by previous research. It is our goal to examine how to best use dual-pol radar data to improve forecast of severe storm and forecast initialization. In recent years, the Development Testbed Center (DTC) has released the community Gridpoint Statistical Interpolation (GSI) DA system for the Weather Research and Forecasting (WRF) model. The community GSI system runs in independently environment, yet works functionally equivalent to operational centers. With collaboration with the NASA Short-term Prediction Research and Transition (SPoRT) Center, this study explores regional assimilation of the dual-pol radar variables from the WSR-88D radars for real case storms. Our presentation will highlight our recent effort on incorporating the horizontal reflectivity (ZH), differential reflectivity (ZDR), specific differential phase (KDP), and radial velocity (VR) data for initializing convective storms, with a significant focus being on an improved representation of hydrometeor fields. In addition, discussion will be provided on the development of enhanced assimilation procedures in the GSI system with respect to dual-pol variables. Beyond the dual-pol variable assimilation procedure developing within a GSI framework, highresolution (≤1 km) WRF model simulations and storm scale data assimilation experiments will be examined, emphasizing both model initialization and short-term forecast of precipitation fields and processes. Further details of the methodology of data assimilation, the impact of different dual-pol variables, the influence on precipitation forecast will be presented at the conference.

Li, Xuanli↗
NASA NTRS2019

An upgraded G-band differential absorption radar system for future airborne studies

A proof-of-concept, 170 GHz frequency-modulated, continuous-wave (FMCW) radar has been developed for measuring water vapor profiles within the cloudy boundary layer from an airborne platform. The measurement concept exploits the differential absorption accrued by two or more transmitted frequencies in the vicinity of the 183 GHz water absorption line to retrieve range-resolved humidity profiles, so-called differential absorption radar (DAR). The upgraded system design includes important considerations for monostatic radar operation with an open fuselage viewport (i.e. no radome). The radar features an all-solid-state tansmitter with > 0:4 W continuous transmit power, a 60 cm primary aperture and corresponding 58 dB antenna gain, and more than 80 dB transmit/receive isolation, enabling near thermal-noise-limited sensitivity with a 8 dB noise figure receiver. Ice-cloud radar returns are detected beyond 8 km in height from the ground, demonstrating the high sensitivity of the system. In addition to in-cloud humidity profiling capabilities, deployment of a water vapor DAR from an airborne platform enables measurements of total column water vapor (TCWV) for all weather and surface scenarios. Precision estimates and potential biases for future TCWV measurements are discussed.

Monje, Raquel↗
NASA NTRSDate not supplied

GLDAS-2 Land Surface Model Data and Data Services at NASA GES DISC

The goal of the NASA Global Land Data Assimilation System (GLDAS, https://ldas.gsfc.nasa.gov/gldas(https://ldas.gsfc.nasa.gov/gldas)) is to generate optimal fields of land surface states and fluxes by ingesting satellite- and ground-based observational data products, using advanced land surface modeling and data assimilation techniques (Rodell et al., 2004).The GLDAS dataset currently archived at and distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC, https://disc.gsfc.nasa.gov/ (https://disc.gsfc.nasa.gov/)) is GLDAS Version 2 (GLDAS-2). It contains a series of output fields from the upgraded Noah-3.6, Catchment-F2.5, and VIC-4.1.2 Land Surface Models (LSMs) in the Land Information System (LIS-V7, https://lis.gsfc.nasa.gov/ (https://lis.gsfc.nasa.gov/)). GLDAS-2 has three components:GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the upgraded Princeton Meteorological ForcingV2.2 Dataset and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data, with data spanning from 2000 to the present. The GLDAS-2.2 product suite uses data assimilation(DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, varies for different GLDAS-2.2 products. The currently availableGLDAS-2.2 data contain a daily 0.25-degree output from the Catchment-F2.5 LSM in LIS-V7. The data are forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (ECMWF-IFS) and assimilated with GRACE and GRACE-FO data, ranging from February 1, 2003 to the present. The current GLDAS-2.0 and 2.1 Noah LSM data were reprocessed in November 2019 and January 2020 respectively and their data from Catchment and VIC LSMs are new to the GLDAS-2 collection. This presentation provides a summary of theGLDAS-2 data products, their land surface fields, and their related data services at the GES DISC; and a description of the majorGLDAS-2 climatological characteristics as well as the intercomparison with the data of the previous version.

Hydrology↗
DOE OSTI2023

Multifamily Building Stock Modeling: Cooperative Research and Development Final Report, CRADA Number CRD-17-00701

U.S. multifamily buildings house 35 million households, consuming 4 quads of source energy and spending $48 billion on utility bills every year. Almost all of these households live in urban areas, where cities are taking the lead on setting aggressive energy goals. Cities currently do not have the data and tools necessary to identify and target opportunities to save energy in their building stock. Building on the open-source, OpenStudio-based ResStock platform, this project will extend the publicly-available ResStock modeling capabilities to the multifamily sector, enabling Radiant Labs, and others, to partner with cities to market and strategically deploy cost-effective, energy efficiency (EE) upgrades directly to high-priority households. Radiant Labs has been successful in using ResStock's single-family capabilities to provide value to the City of Boulder, Colorado. However, lack of multifamily capabilities in ResStock is a roadblock for Radiant Labs working with New York City, San Francisco, Washington, D.C., and other cities that have expressed significant interest in working with them. In addition, other cities, companies, and utilities can use these open-source capabilities to grow their EE portfolios, thereby multiplying the impact of this project. This work also enables national-scale analysis of EE potential in multifamily buildings, which is of strong interest to a variety of stakeholders, including the U.S. Department of Energy (DOE) Office of Energy Policy and Systems Analysis (EPSA), DOE Weatherization Assistance Program (WAP), U.S. Department of Housing and Urban Development (HUD), and the Bonneville Power Administration (BPA).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2002

Forecasting Coronal Mass Ejections from Vector Magnetograms

Identification of active regions from which Earthward halo Coronal Mass Ejections (CMEs) are likely to originate is important both for understanding how CMEs are produced and for prediction of hazardous space weather. In previous work, from a set of 17 MSFC (Marshall Space Flight Center) vector magnetograms of 12 bipolar active regions situated within +/- 2 days of rotation from central meridian, we have evaluated four different measures of the global nonpotentiality of the magnetic field of each active region, and have found that the nonpotentiality of these active regions is strongly correlated with their CME productivity during the time interval of +/- 2 days centered on the day of the magnetogram: strongly nonpotential bipolar active regions are much more likely to produce a CME during this interval that are weakly nonpotential bipolar active regions. To further establish the use of active-region nonpotentiality for forecasting CMEs, we have expanded the sample to 19 additional bipolar active regions, with vector magnetograms taken with the upgraded MSFC vector magnetograph from September 2000 through June 2001 with support from our LWS grant (M. J. Hagyard, PI). The four global measures of nonpotentiality are the length of strong-shear, strong-field main neutral line, the net current, and two other measures of the overall twist in the magnetic field of the active-region bipole. We find: 1) The statistical significance of the correlation of the nonpotentiality of active regions with their CME productivity within +/- 2 days of the day of the magnetogram is greater than 99%. 2) 67% of the strongly nonpotential active regions produced CMEs within the +/- 2 day window, while only 17% of the weakly nonpotential ones did. 3) The statistical significance of the correlation of the nonpotentiality of active regions with their CME productivity during 0-2 days after the day of the magnetogram is about 97%. 4) 42% of the strongly nonpotential active regions produced CMEs within the 0-2 day window, while only 10% of the weakly nonpotential ones did. 5) The four different measures of an active region's nonpotentiality agree most of the time in their classification of the nonpotentiality as strong or weak (75%-90% depending on the pair of measurements). Additional information is included in the original extended abstract.

Moore, R. L.↗
NASA NTRS2005

Forecasting Lightning at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

The Applied Meteorology Unit (AMU) developed a set of statistical forecast equations that provide a probability of lightning occurrence on Kennedy Space Center (KSC) I Cape Canaveral Air Force Station (CCAFS) for the day during the warm season (May September). The 45th Weather Squadron (45 WS) forecasters at CCAFS in Florida include a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts, which are briefed at 1100 UTC (0700 EDT). This information is used for general scheduling of operations at CCAFS and KSC. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts for the KSC/CCAFS area during Shuttle flight operations. Much of the current lightning probability forecast at both groups is based on a subjective analysis of model and observational data. The objective tool currently available is the Neumann-Pfeffer Thunderstorm Index (NPTI, Neumann 1971), developed specifically for the KSCICCAFS area over 30 years ago. However, recent studies have shown that 1-day persistence provides a better forecast than the NPTI, indicating that the NPTI needed to be upgraded or replaced. Because they require a tool that provides a reliable estimate of the daily thunderstorm probability forecast, the 45 WS forecasters requested that the AMU develop a new lightning probability forecast tool using recent data and more sophisticated techniques now possible through more computing power than that available over 30 years ago. The equation development incorporated results from two research projects that investigated causes of lightning occurrence near KSCICCAFS and over the Florida peninsula. One proved that logistic regression outperformed the linear regression method used in NPTI, even when the same predictors were used. The other study found relationships between large scale flow regimes and spatial lightning distributions over Florida. Lightning, probabilities based on these flow regimes were used as candidate predictors in the equation development. Fifteen years (1 989-2003) of warm season data were used to develop the forecast equations. The data sources included a local network of cloud-to-ground lightning sensors called the Cloud-to-Ground Lightning Surveillance System (CGLSS), 1200 UTC Florida synoptic soundings, and the 1000 UTC CCAFS sounding. Data from CGLSS were used to determine lightning occurrence for each day. The 1200 UTC soundings were used to calculate the synoptic-scale flow regimes and the 1000 UTC soundings were used to calculate local stability parameters, which were used as candidate predictors of lightning occurrence. Five logistic regression forecast equations were created through careful selection and elimination of the candidate predictors. The resulting equations contain five to six predictors each. Results from four performance tests indicated that the equations showed an increase in skill over several standard forecasting methods, good reliability, an ability to distinguish between non-lightning and lightning days, and good accuracy measures and skill scores. Given the overall good performance the 45 WS requested that the equations be transitioned to operations and added to the current set of tools used to determine the daily lightning probability of occurrence.

Lambert, Winfred↗
DOE OSTI2026

Data Management for Digital Twin Implementation: Enhancing Existing SCADA Architecture for INL's CITRC Test Distribution System

The United States power grid will continue to experience stress from aging infrastructure, extreme weather, and increasing loads. In order to strengthen resiliency, researchers need to run tests and simulations that model real-life infrastructure. Idaho National Laboratory (INL) is creating a digital twin of its Critical Infrastructure Test Range Complex (CITRC). CITRC is an at-scale grid testbed which can be configured in utility-realistic distribution scenarios for a variety of tests, such as advanced grid protection and control. A digital twin of this infrastructure would support in-depth tests/simulations without risking physical consequences, before trialing devices under test at-scale. This project focuses on the data acquisition part of constructing a digital twin. It investigates the Supervisory Data Acquisition and Control (SCADA) system of CITRC and explores ways to utilize this system for the twin. Future “ideal” at-scale implementations such as upgraded equipment, modern communication protocols, and automation applications are also explored.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2018

NASA's Space Launch System: Opportunities for Small Satellites to Deep Space Destinations

The first flight of NASA's new exploration-class launch vehicle, the Space Launch System (SLS), will test a myriad of systems designed to enable the next generation of deep space human spaceflight, while also providing the rare opportunity for 13 6U CubeSat-class payloads to be deployed in several locations along the flight path. The first mission of SLS and NASA's new Orion crew vehicle, Exploration Mission-1 (EM-1), will launch from upgraded facilities at Kennedy Space Center no earlier than fiscal year 2020. The initial Block 1 configuration for EM-1 will be capable of lofting at least 26 metric tons (t) of payload to the moon, with propulsion supplied by twin five-segment solid rocket boosters, four RS-25 engines and an Interim Cryogenic Propulsion Stage (ICPS). SLS will send Orion into a distant retrograde lunar orbit, paving the way for future missions to cislunar space and eventually Mars. The multidisciplinary small satellites for EM-1 derive from NASA research, as well as from international partners, industry and academia. Research subjects for the various smallsats include the moon, sun and an asteroid. Science objectives vary from characterizing the effects of radiation on living organisms (yeast) to landing the smallest spacecraft yet on the moon to supporting space weather research. Some of the payloads are technology demonstrations that will pave the way for more ambitious future missions that will be deployed by the more powerful SLS Block 1B configuration.

Robinson, Kimberly F.↗
DOE OSTI2026

Repowering: The Other Side of the Reliability Coin

Extreme weather, cracked backsheets, severe PID, poorly built modules, and installation flaws - all can compromise a solar plant's health and force repowering long before end of life. With more than 70% of U.S. PV capacity less than seven years old, the fleet is young, but its rapid expansion has introduced new materials and system designs that are still being tested under real-world conditions. As a result, reliability - not economics - is what most often drives repowering decisions. Repowering is frequently assumed to be an economically motivated choice, but our work shows that reliability concerns are the real trigger. Drawing from industry interviews, case studies, and modeling, we highlight the physical, electrical, and policy barriers owners face when deciding whether to repair, repower, or decommission. At the same time, repowering can create opportunities: renewed interconnection periods, improved energy yields, and strategic upgrades to extend system value. We present a quantitative framework using NLR's System Advisor Model (SAM) and PV in Circular Economy (PV ICE) tool to evaluate trade-offs across financial, material, and energy impacts. These findings provide practical guidance for navigating the realities of repowering today and underscore the critical role of reliability in shaping the future performance and sustainability of the PV fleet.

14 SOLAR ENERGY↗
NASA NTRS1992

Acquisition and use of Orlando, Florida and Continental Airbus radar flight test data

Westinghouse is developing a lookdown pulse Doppler radar for production as the sensor and processor of a forward looking hazardous windshear detection and avoidance system. A data collection prototype of that product was ready for flight testing in Orlando to encounter low level windshear in corroboration with the FAA-Terminal Doppler Weather Radar (TDWR). Airborne real-time processing and display of the hazard factor were demonstrated with TDWR facilitated intercepts and penetrations of over 80 microbursts in a three day period, including microbursts with hazard factors in excess of .16 (with 500 ft. PIREP altitude loss) and the hazard factor display at 6 n.mi. of a visually transparent ('dry') microburst with TDWR corroborated outflow reflectivities of +5 dBz. Range gated Doppler spectrum data was recorded for subsequent development and refinement of hazard factor detection and urban clutter rejection algorithms. Following Orlando, the data collection radar was supplemental type certified for in revenue service on a Continental Airlines Airbus in an automatic and non-interferring basis with its ARINC 708 radar to allow Westinghouse to confirm its understanding of commercial aircraft installation, interface realities, and urban airport clutter. A number of software upgrades, all of which were verified at the Receiver-Transmitter-Processor (RTP) hardware bench with Orlando microburst data to produce desired advanced warning hazard factor detection, included some preliminary loads with automatic (sliding window average hazard factor) detection and annunciation recording. The current (14-APR-92) configured software is free from false and/or nuisance alerts (CAUTIONS, WARNINGS, etc.) for all take-off and landing approaches, under 2500 ft. altitude to weight-on-wheels, into all encountered airports, including Newark (NJ), LAX, Denver, Houston, Cleveland, etc. Using the Orlando data collected on hazardous microbursts, Westinghouse has developed a lookdown pulse Doppler radar product with signal and data processing algorithms which detect realistic microburst hazards and has demonstrated those algorithms produce no false alerts (or nuisance alerts) in urban airport ground moving vehicle (GMTI) and/or clutter environments.

Eide, Michael C.↗
DOE OSTI2021

Transportation Fuel Resiliency: Case Study of Tampa Bay

Here, this case study presents findings from an analysis of the emergency preparation and response for Hurricane Irma, the most recent hurricane impacting the Tampa Bay region. The Tampa Bay region, in particular, is considered one of the most vulnerable areas in the United States to hurricanes and severe tropical weather. A particular vulnerability stems from how all petroleum fuel comes to the area by marine transport through Port Tampa Bay, which can be (and has been in the past) impacted by hurricanes and tropical storms. The case study discussed in this paper covers previous fuel challenges, vulnerabilities, and lessons learned by key Tampa Bay public agency fleets during the past 10 years (mainly as a result of the most recent 2017 Hurricane Irma) to explore ways to improve the area’s resilience to natural disasters. Some of the strategies for fuel-supply resiliency include maintaining emergency fuel supply, prioritizing fuel use, strategically placing the assets around the region to help with recovery, investing in backup generators (including generators powered by alternative fuels), planning for redundancies in fuel supply networks, developing more efficient communication procedures between public fleets, hurricane preparedness-planning, and upgrading street drainage systems to reduce the threat of local flooding.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2016

Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 Systems

The purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.

NLDAS-2↗
DOE OSTI2020

SYMBA: An end-to-end VLBI synthetic data generation pipeline

Realistic synthetic observations of theoretical source models are essential for our understanding of real observational data. In using synthetic data, one can verify the extent to which source parameters can be recovered and evaluate how various data corruption effects can be calibrated. These studies are the most important when proposing observations of new sources, in the characterization of the capabilities of new or upgraded instruments, and when verifying model-based theoretical predictions in a direct comparison with observational data. We present the SYnthetic Measurement creator for long Baseline Arrays (SYMBA), a novel synthetic data generation pipeline for Very Long Baseline Interferometry (VLBI) observations. SYMBA takes into account several realistic atmospheric, instrumental, and calibration effects. Here, we used SYMBA to create synthetic observations for the Event Horizon Telescope (EHT), a millimetre VLBI array, which has recently captured the first image of a black hole shadow. After testing SYMBA with simple source and corruption models, we study the importance of including all corruption and calibration effects, compared to the addition of thermal noise only. Using synthetic data based on two example general relativistic magnetohydrodynamics (GRMHD) model images of M 87, we performed case studies to assess the image quality that can be obtained with the current and future EHT array for different weather conditions. Our synthetic observations show that the effects of atmospheric and instrumental corruptions on the measured visibilities are significant. Despite these effects, we demonstrate how the overall structure of our GRMHD source models can be recovered robustly with the EHT2017 array after performing calibration steps, which include fringe fitting, a priori amplitude and network calibration, and self-calibration. With the planned addition of new stations to the EHT array in the coming years, images could be reconstructed with higher angular resolution and dynamic range. In our case study, these improvements allowed for a distinction between a thermal and a non-thermal GRMHD model based on salient features in reconstructed images.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hydroclimate-coupled framework for assessing power system resilience under summer drought and climate change

Extreme drought, exacerbated by climate change, increasingly threatens power system resilience, and a systematic assessment of such impacts is challenging due to the unpredictability of drought and their associated modeling complexity. Here, to address the challenge, this research develops a hydroclimate-coupled power system resilience assessment framework that enables systematic modeling of drought and climate change impacts on generation, transmission, and demand sectors. Applying the framework to the 2025 Eastern U.S. power grid — comprising 6,055 at-risk generators — under climate-induced summer drought scenarios (including SSP126, SSP245, SSP370, and SSP585) from 2023 to 2100, the study finds that climate-induced droughts could jeopardize the power system’s reliability to a greater extent than historical events, potentially leading to widespread load shedding. More specifically, the study reveals that under the twenty-one representative drought scenarios, the loss of load expectation (LOLE) of the grid could range from 34.77 to 91.48 days per summer. The simulations indicate that implementing resilience enhancement strategies is crucial to ensure reliable system operation, which encompasses initiatives such as demand response, upgrading open cooling systems, and transmission expansion. In all, these findings underscore the urgent need for proactive planning and investment in resilient U.S. power systems to mitigate the impacts of extreme drought events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Evaluating Diesel/Biofuel Blends Using Artificial Neural Networks and Linear/Nonlinear Equations

Abstract The use of biomass-derived additives in diesel fuel mixtures has the potential to increase the fuel’s efficiency, decrease the formation of particulate matter during its combustion, and retain the fuel’s behavior in cold weather. To this end, identifying compounds that enable these behaviors is paramount. The present work utilizes a series of linear and non-linear equations in series with artificial neural networks to predict the cetane number, yield sooting index, kinematic viscosity, cloud point, and lower heating value of multi-component blends. Property values of pure components are predicted using artificial neural networks trained with existing experimental data, and these predictions and their expected errors are propagated through linear and non-linear equations to obtain property predictions for multi-component blends. Individual component property prediction errors, defined by blind prediction median absolute error, are 4.91 units, 7.84 units, 0.06 cSt, 4.00 °C, and 0.55 MJ/kg for cetane number, yield sooting index, kinematic viscosity, cloud point, and lower heating value respectively. On average, property predictions for blends are shown to be accurate to within 6% of the blends’ experimental values. Further, a multitude of compounds expected to be produced from catalytically upgrading products of fast pyrolysis are evaluated with respect to their behavior in diesel fuel blends.

09 BIOMASS FUELS↗
DOE OSTI2020

Foundations of an Electric Mobility Strategy for the City of Mexicali

The Foundations of an Electric Mobility Strategy for the city of Mexicali aligns with numerous energy, environmental, and transport plans and will help Mexicali meet multiple related goals. Mexicali’s energy mix, with 28% renewables, already enables plugin electric vehicles (PEVs) to reduce the mass of greenhouse gases (GHGs) per km driven 2/3 below that of their conventional counterparts. This GHG benefit will increase should Mexicali take steps to further increase their share of renewables in their electricity supply. Beyond increasing renewables, Mexicali could possibly deploy PEVs so that electric load is added in the right location (depending on further analysis of substations and feeders) and at the right time (between 21:00 and 11:00) in order to minimize grid upgrade costs. There are a handful of charge timing control mechanisms –at various stages of development– that Mexicali could implement. Transport electrification can facilitate mass transit by powering buses, trains, and small vehicles that get people from their homes or work to the transit stations and vice versa. Mexicali could utilize fleets as early PEV adopters in order to gain acceptance and add electric vehicle supply equipment (EVSE). Recommended prioritization of different types of fleets are suggested in this report: transit buses, school buses, airport ground support equipment (GSE), refuse trucks, taxis, shuttle buses, campus vehicles, delivery trucks, utility trucks, and finally semitrailers. There are a handful of policy options that Mexicali could use to incentivize fleets to purchase PEVs, including mandates, economic incentives, energy performance contracts, waivers to access restrictions, electricity discounts, and EVSE requirements in building codes. Mexicali’s taxi fleet was an early adopter of PEVs and had experienced some challenges—mostly related to the insufficient range of the taxis due to hot weather. In this report, we strategize ways to extend the range of the current electric taxis, including ways to make charging more convenient to the drivers, and more suggestions for appropriate vehicles to purchase in the future. This report also includes the groundwork of geotracking Mexicali’s taxi fleet so that more detailed recommendations can be made in the future. Once fleets have increased PEV acceptance and EVSE installations, the market will be ready to expand to private vehicle owners. In order to do this, more EVSE needs to be installed in the right locations. This mobility strategy lays out general local areas where EVSE could be well utilized, based on traffic patterns, land use, and demographic data. Mexicali could approach businesses within these areas that would likely make suitable hosts, based on how well they can profit from the additional business that EVSE would bring. Mexicali could then adopt a series of purchase incentives (including sales tax waivers or access to high-occupancy vehicles [HOV] lanes) that would encourage private vehicle owners to purchase PEVs. Purchase incentives run the risk of creating equity issues, which can be countered by promoting electrification in mass transit, creating more HOV lanes that have PEV exemptions, and installing EVSEs in underserved communities. Private PEV ownership will require a set of experts that Mexicali can help train, including PEV repair technicians, EVSE installation electricians, and first responders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Should Sea-Ice Modeling Tools Designed for Climate Research Be Used for Short-Term Forecasting?

In theory, the same sea-ice models could be used for both research and operations, but in practice, differences in scientific and software requirements and computational and human resources complicate the matter. Although sea-ice modeling tools developed for climate studies and other research applications produce output of interest to operational forecast users, such as ice motion, convergence, and internal ice pressure, the relevant spatial and temporal scales may not be sufficiently resolved. For instance, sea-ice research codes are typically run with horizontal resolution of more than 3 km, while mariners need information on scales less than 300 m. Certain sea-ice processes and coupled feedbacks that are critical to simulating the Earth system may not be relevant on these scales; and therefore, the most important model upgrades for improving sea-ice predictions might be made in the atmosphere and ocean components of coupled models or in their coupling mechanisms, rather than in the sea-ice model itself. This paper discusses some of the challenges in applying sea-ice modeling tools developed for research purposes for operational forecasting on short time scales, and highlights promising new directions in sea-ice modeling.

54 ENVIRONMENTAL SCIENCES↗