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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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NASA NTRS1972

Mars lander position estimation in the presence of ephemeris biases.

The process of estimating the location of a spacecraft landed on the surface of Mars is investigated through the application of statistical estimation techniques to earth-based radio tracking data. The spacecraft location and the tracking geometry and schedule are consistent with Viking-type mission constraints. With mission control requirements in mind, the investigation is restricted to analysis of a short data arc (approximately 3 days). Statistics of the spacecraft location are obtained through analysis of (direct-link) tracking data for the landed spacecraft and through simultaneous analysis of tracking data for both a landed and an orbiting spacecraft. These estimates include the effects of model uncertainties in the ephemeris of Mars, tracking station locations, the Mars rotational period, the Mars gravity field, and the orientation of Mars axis of rotation. The most significant of these effects is shown to be due to the Mars ephemeris uncertainty. A dual spacecraft tracking technique is presented for substantially reducing these ephemeris effects.

Blackshear, W. T.↗

NASA NTRS1978

A rotor-mounted digital instrumentation system for helicopter blade flight research measurements

A rotor mounted flight instrumentation system developed for helicopter rotor blade research is described. The system utilizes high speed digital techniques to acquire research data from miniature pressure transducers on advanced rotor airfoils which are flight tested on an AH-1G helicopter. The system employs microelectronic pulse code modulation (PCM) multiplexer digitizer stations located remotely on the blade and in a hub mounted metal canister. As many as 25 sensors can be remotely digitized by a 2.5 mm thick electronics package mounted on the blade near the tip to reduce blade wiring. The electronics contained in the canister digitizes up to 16 sensors, formats these data with serial PCM data from the remote stations, and transmits the data from the canister which is above the plane of the rotor. Data are transmitted over an RF link to the ground for real time monitoring and to the helicopter fuselage for tape recording. The complete system is powered by batteries located in the canister and requires no slip rings on the rotor shaft.

Knight, V. H., Jr.↗

DOE OSTI2020

Geothermal Data Gap Analysis Over the Western US

NREL, as part of the Play Fairway Analysis Retrospective, compiled and mapped publicly available geologic and geophysical data in relation to the 2008 USGS geothermal potential analysis. Included in this submission are maps displaying the publicly available data for LIDAR coverage, aeromagnetic coverage, gravity station locations, and geologic map coverage over the Western United States.

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

A Short-Term Solar Forecasting Platform Using a Physics-Based Smart Persistence Model and Data Imputation Method

Electrical energy plays vital role in our socio-economic activity and therefore ensuring the reliability of the electric grid, from the generation, transmission and distribution level is critical. In order to maintain the power system parameter viz., frequency, voltage, etc., optimally, balancing of generation and consumption is very much essential. However, solar energy is infirm power by nature this is due to cloud cover / other local phenomena. Hence, Photovoltaic (PV) power generation brings a significant challenge to the grid operator due to the variability of the solar energy. The complexity of this challenge in terms of planning and dispatch ability of PV resources, aggravates with the high penetration of solar energy into the electric grid. In this setting, reliable solar radiation forecasting models based on accurate and quality input data become essential. In order to develop a suitable model for predicting solar radiation, quality historical / real time measurement is also needed. Under this study NIWE and NREL jointly developed / tested short-term solar forecasting frameworks using a smart persistence and physics-based smart persistence models for intra-hour forecasting of solar radiation (PSPI) and benchmarked 9 different data imputation techniques in 15 Solar Radiation Resource Assessment (SRRA) stations, located at different parts of India. During any measurement campaign, due to various technical reasons, we may miss few observations. However, the missing observation often reduce the performance of any forecasting model. Therefore, suitable data imputation method would assist us to obtain continuous observation of solar radiation. A station-by-station and method-by-method analysis was carried out to understand the performance of each model. Based on our analysis, among all the data imputation methods, the Kalman data imputation method is better for Indian Weather condition. In addition, Kalman StructTS, Linear, Stine and Arima methods yield slightly inferior accuracy compared to Kalman, but outperform the other methods. The extended solar radiation data are used by solar forecasting models to provide the prediction of solar radiation at 15 SRRA stations. As far as short term forecasting model is concerned, the PSPI model outperforms the Smart Persistence model. However, the forecast error is increases with the forecasting horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2013

2011 Mars Science Laboratory Trajectory Reconstruction and Performance from Launch Through Landing

The Mars Science Laboratory (MSL) mission successfully launched on an Atlas V 541 Expendable Evolved Launch Vehicle (EELV) from the Eastern Test Range (ETR) at Cape Canaveral Air Force Station (CCAFS) in Florida at 15:02:00 UTC on November 26th, 2011. At 15:52:06 UTC, six minutes after the MSL spacecraft separated from the Centaur upper stage, the spacecraft transmitter was turned on and in less than 20 s spacecraft carrier lock was achieved at the Universal Space Network (USN) Dongara tracking station located in Western Australia. MSL, carrying the most sophisticated rover ever sent to Mars, entered the Martian atmosphere at 05:10:46 SpaceCraft Event Time (SCET) UTC, and landed inside Gale Crater at 05:17:57 SCET UTC on August 6th, 2012. Confirmation of nominal landing was received at the Deep Space Network (DSN) Canberra tracking station via the Mars Odyssey relay spacecraft at 05:31:45 Earth Received Time (ERT) UTC. This paper summarizes in detail the actual vs. predicted trajectory performance in terms of launch vehicle events, launch vehicle injection performance, actual DSN/USN spacecraft lockup, trajectory correction maneuver performance, Entry, Descent, and Landing events, and overall trajectory and geometry characteristics.

trajectory↗

NASA NTRS2019

Quantifying Water Storage Change and Land Subsidence Induced by Reservoir Impoundment Using GRACE, Landsat, and GPS Data

The construction of hydropower dams is a common strategy to support a country's increasing need for electricityand river water management for industry and agriculture. Although the hydrological and geophysical impacts ofwater relocation are usually assessed prior to impoundment, their accuracy is generally limited due to the lack ofin situ observations, especially in a remote area. This study presents a workflow to quantify the terrestrial waterstorage change (TWS) and land subsidence induced by a reservoir's water impoundment using multiple satelliteobservations (GRACE, Landsat), land surface models (CABLE, GLDAS, NCEP, ECMWF), and GPS data. The studysite is the Bakun Dam, located in Sarawak, Malaysia, which is the largest hydropower dam in Southeast Asia.Commencing operation in late 2010, the dam induced a change of water mass and lake surface area that wasclearly observed by GRACE and Landsat observations, respectively. During the 17-month impounding period(from August 2010 to December 2011), GRACE observed a dramatic increase of approximately 200mmequivalent water height, while Landsat detected an increased lake extent of around 600 km2. In this paper, aforward model is developed to determine the increased water surface level corresponding to GRACE observations,estimated to be about 120 m. In contrast to GRACE, the TWS derived from land surface models cannotcapture the increased TWS, due to the lack of reservoir routing algorithms in the models. In addition, the landsubsidence was calculated using the disk load model constructed based on the GRACE-derived lake level andLandsat-derived lake extent; the result is validated with the GPS data from BIN1 station, located at the westerncoast of Borneo. The commencement stage of the Bakun Dam induces the large-scale land subsidence, whichcauses the GPS-BIN1 station to subside by ~9 mm, and move toward the Bakun Lake by ~4 mm. Computation ofthe surface displacements directly from GRACE spherical harmonic coefficient data fails to capture the subsidencefeature, mainly due to the truncation error. Overall, this study demonstrates that evaluating GRACE inconjunction with Landsat, LSMs, and GPS data allows the exploitation of the gravity signal at a much smallerspatial scale than its intrinsic resolution. Benefiting from global coverage, the newly developed satellite-basedalgorithm is a valuable tool for assessing the impacts of reservoir operation on hydrological and geophysicalchanges from local to regional scales.

Tangdamrongsub, Natthachet↗

NASA NTRS2019

Quantifying Water Storage Change and Land Subsidence Induced by Reservoir Impoundment Using GRACE, Landsat, and GPS Data

The construction of hydropower dams is a common strategy to support a country's increasing need for electricity and river water management for industry and agriculture. Although the hydrological and geophysical impacts of water relocation are usually assessed prior to impoundment, their accuracy is generally limited due to the lack of in situ observations, especially in a remote area. This study presents a workflow to quantify the terrestrial water storage change (TWS) and land subsidence induced by a reservoir's water impoundment using multiple satellite observations (GRACE, Landsat), land surface models (CABLE, GLDAS, NCEP, ECMWF), and GPS data. The study site is the Bakun Dam, located in Sarawak, Malaysia, which is the largest hydropower dam in Southeast Asia. Commencing operation in late 2010, the dam induced a change of water mass and lake surface area that was clearly observed by GRACE and Landsat observations, respectively. During the 17-month impounding period (from August 2010 to December 2011), GRACE observed a dramatic increase of approximately 200 mm equivalent water height, while Landsat detected an increased lake extent of around 600 km2. In this paper, a forward model is developed to determine the increased water surface level corresponding to GRACE observations, estimated to be about 120 m. In contrast to GRACE, the TWS derived from land surface models cannot capture the increased TWS, due to the lack of reservoir routing algorithms in the models. In addition, the land subsidence was calculated using the disk load model constructed based on the GRACE-derived lake level and Landsat-derived lake extent; the result is validated with the GPS data from BIN1 station, located at the western coast of Borneo. The commencement stage of the Bakun Dam induces the large-scale land subsidence, which causes the GPS-BIN1 station to subside by ~9 mm, and move toward the Bakun Lake by ~4 mm. Computation of the surface displacements directly from GRACE spherical harmonic coefficient data fails to capture the subsidence feature, mainly due to the truncation error. Overall, this study demonstrates that evaluating GRACE in conjunction with Landsat, LSMs, and GPS data allows the exploitation of the gravity signal at a much smaller spatial scale than its intrinsic resolution. Benefiting from global coverage, the newly developed satellite-based algorithm is a valuable tool for assessing the impacts of reservoir operation on hydrological and geophysical changes from local to regional scales.

Natthachet Tangdamrongsub↗

NASA NTRS1995

Helmet-Mounted Display Research Capabilities of the NASA/Army Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL)

The Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) is a UH-60A Black Hawk helicopter that is being modified by the US Army and NASA for flight systems research. The principal systems that are being installed in the aircraft are a Helmet Mounted Display (HMD) and imaging system, and a programmable full authority Research Flight Control System (RFCS). In addition, comprehensive instrumentation of both the rigid body of the helicopter and the rotor system is provided. The paper will describe the capabilities of these systems and their current state of development. A brief description of initial research applications is included. The wide (40 X 60 degree) field-of-view HMD system has been provided by Kaiser Electronics. It can be configured as a monochromatic system for use in bright daylight conditions, a two color system for darker ambients, or a full color system for use in night viewing conditions. Color imagery is achieved using field sequential video and a mechanical color wheel. In addition to the color symbology, high resolution computer-gene rated imagery from an onboard Silicon Graphics Reality Engine Onyx processor is available for research in virtual reality applications. This synthetic imagery can also be merged with real world video from a variety of imaging systems that can be installed easily on the front of the helicopter. These sensors include infrared or tv cameras, or potentially small millimeter wave radars. The Research Flight Control System is being developed for the aircraft by a team of contractors led by Boeing Helicopters. It consists of a full authority high bandwidth fly-by-wire actuators that drive the main rotor swashplate actuators and the tail rotor actuator in parallel. This arrangement allows the basic mechanical flight control system of the Black Hawk to be retained so that the safety pilot can monitor the operation of the system through the action of his own controls. The evaluation pilot will signal the fly-by-wire actuators through the flight computer from electrical sidearm controllers located in the right hand cockpit. The system will have very substantial input/output capacity and impressive computational power. These systems are installed in the aircraft using predominantly a MIL-STD 1553B data bus architecture. Sensor data from the RFCS, the basic aircraft and rotor system instrumentation including navigation information, and the HMD system are easily exchanged among user systems, or are available at the systems operator station located in the cabin for real time monitoring or data recording.

Jacobsen, R. A.↗

DOE OSTI2020

Quarterly Technical Progress Report Piperazine Advanced Stripper (PZAS™) Front End Engineering Design

EXECUTIVE SUMMARY This document summarizes the status of Cooperative Agreement DE-FE0031844, “Piperazine Advanced Stripper (PZAS™) Front-End Engineering Design,” during the reporting period of January 1 through March 31, 2020. The objective of this project is to develop accurate installed costs by conducting a Front-End Engineering Design (FEED) of PZAS™ at Golden Spread Electric Cooperative’s (GSEC) Mustang Station located in Denver City, TX. Complementary benefits include positioning the technology for a commercial project with the 45Q tax credits, qualifying PZAS™ for use on a Natural Gas Combined Cycle (NGCC) Cogen facility, and to provide cost detail to optimize PZAS™ and help guide R&D of second-generation solvent CO2 capture technologies. Results from the FEED will be used to evaluate the economic feasibility of the process at Mustang Station. This project is funded by the U.S. DOE National Energy Technology Laboratory under the aforementioned Cooperative Agreement. Exxon, Total, Chevron, UOP-Honeywell, and the University of Texas (UT) are project co-funders. AECOM and Trimeric are project team members; UT is the prime contractor. Summary of Progress Cooperative Agreement DE-FE0031844 was established in October 2019. The current reporting period, January 1 through March 31, 2020, is the second technical progress reporting period for the project. Several milestones were accomplished during this reporting period, including: • Kickoff Meeting with DOE on February 3, 2020. • Kickoff Meeting with GSEC on March 30, 2020. (Note: Due to Covid-19 travel restrictions and shelter-in-place guidelines, the kickoff meeting was conducted remotely via videoconferencing. See attached notes from that telecon.) • Updated Project Management Plan March 2020, submitted with this quarterly report Other activities during the quarter included progress on contracting and other legal agreements (e.g., non-disclosure agreements), internal kickoff meetings at both AECOM and Trimeric, and development of a Technical Implementation Plan (TIP). The TIP will help the team to make critical, early process decisions and, ultimately, to develop a project and process design basis. Note that all agreements between project team participants are complete as of this submittal, except the vendor agreement with Kiewit (steam cycle modeling). Plans for Next Reporting Period Activities during the next reporting period (April 1, 2020 through June 30, 2020) include: the completion of the Project Design Basis and progress towards the Process Design Basis/Process Design Package (PDP). The Project Design Basis is due as a deliverable and milestone during the next reporting period.

Rochelle, Gary T.↗

NASA NTRS1989

Estimation and filtering techniques for high-accuracy GPS applications

Techniques for determination of very precise orbits for satellites of the Global Positioning System (GPS) are currently being studied and demonstrated. These techniques can be used to make cm-accurate measurements of station locations relative to the geocenter, monitor earth orientation over timescales of hours, and provide tropospheric and clock delay calibrations during observations made with deep space radio antennas at sites where the GPS receivers have been collocated. For high-earth orbiters, meter-level knowledge of position will be available from GPS, while at low altitudes, sub-decimeter accuracy will be possible. Estimation of satellite orbits and other parameters such as ground station positions is carried out with a multi-satellite batch sequential pseudo-epoch state process noise filter. Both square-root information filtering (SRIF) and UD-factorized covariance filtering formulations are implemented in the software.

Lichten, S. M.↗

DOE OSTI2022

DeepShake: Shaking Intensity Prediction Using Deep Spatiotemporal RNNs for Earthquake Early Warning

Abstract We propose a deep spatiotemporal recurrent neural network, DeepShake, to project future shaking intensity directly from current ground-motion observations. DeepShake is a network-based forecasting model, able to predict future shaking intensity at all stations within a network given previously measured ground shaking. The model is not given any a priori knowledge of station locations; instead, it learns wave propagation amplitudes and delays solely from training data. We developed DeepShake with the 35,679 earthquakes from the 2019 Ridgecrest sequence. Tasked with alerting for modified Mercalli intensity (MMI) IV+ shaking on 3568 validation earthquakes at least 5 s in advance, DeepShake achieves an equal error rate of 11.4%. For the Mw 7.1 earthquake that hit Ridgecrest on 5 July 2019, DeepShake was able to provide targeted alerts to all stations inside the network 5 s prior to the arrival of MMI IV+ waveforms. DeepShake demonstrates that deep spatiotemporal neural networks can effectively provide one-step earthquake early warning with reasonable accuracy and latency.

Geochemistry & Geophysics↗

NASA NTRS2019

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer.

cloud droplets↗

NASA NTRS1984

Basic Features of Global Circulation in the Mesopause Lower Thermosphere Region

D1 and D2 techniques have been used and are being used for observations at stations located in the high, middle, and low latitudes of both hemispheres. The systematical and wind velocity measurements with these techniques make it possible to specify and to refine earlier mesopause-lower thermosphere circulation models. With this in view, an effort was made to obtain global long term average height-latitude sections of the wind field at 70 to 110 km using the analysis of long period D1 and D2 observations. Data from 26 meteor radar and 6 ionospheric stations were taken for analysis.

Portnyagin, Y. I.↗

DOE OSTI2022

Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations

In 2015 and 2016, atmospheric transport modeling challenges were conducted in the context of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) verification, however, with a more limited scope with respect to emission inventories, simulation period and number of relevant samples (i.e., those above the Minimum Detectable Concentration (MDC)) involved. Therefore, a more comprehensive atmospheric transport modeling challenge was organized in 2019. Stack release data of Xe-133 were provided by the Institut National des Radioéléments/IRE (Belgium) and the Canadian Nuclear Laboratories/CNL (Canada) and accounted for in the simulations over a three (mandatory) or six (optional) months period. Best estimate emissions of additional facilities (radiopharmaceutical production and nuclear research facilities, commercial reactors or relevant research reactors) of the Northern Hemisphere were included as well. Model results were compared with observed atmospheric activity concentrations at four International Monitoring System (IMS) stations located in Europe and North America with overall considerable influence of IRE and/or CNL emissions for evaluation of the participants’ runs. Participants were prompted to work with controlled and harmonized model set-ups to make runs more comparable, but also to increase diversity. It was found that using the stack emissions of IRE and CNL with daily resolution does not lead to better results than disaggregating annual emissions of these two facilities taken from the literature if an overall score for all stations covering all valid observed samples is considered. A moderate benefit of roughly 10% is visible in statistical scores for samples influenced by IRE and/or CNL to at least 50% and there can be considerable benefit for individual samples. Effects of transport errors, not properly characterized remaining emitters and long IMS sampling times (12–24 h) undoubtedly are in contrast to and reduce the benefit of high-quality IRE and CNL stack data. Complementary best estimates for remaining emitters push the scores up by 18% compared to just considering IRE and CNL emissions alone. Despite the efforts undertaken the full multi-model ensemble built is highly redundant. An ensemble based on a few arbitrary runs is sufficient to model the Xe-133 background at the stations investigated. The effective ensemble size is below five. An optimized ensemble at each station has on average slightly higher skill compared to the full ensemble. However, the improvement (maximum of 20% and minimum of 3% in RMSE) in skill is likely being too small for being exploited for an independent period.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1991

SPECS: Orbital debris removal

The debris problem has reached a stage at which the risk to satellites and spacecraft has become substantial in low Earth orbit (LEO). This research discovered that small particles posed little threat to spacecraft because shielding can effectively prevent these particles from damaging the spacecraft. The research also showed that, even though collision with a large piece of debris could destroy the spacecraft, the large pieces of debris pose little danger because they can be tracked and the spacecraft can be maneuvered away from these pieces. Additionally, there are many current designs to capture and remove large debris particles from the space environment. From this analysis, it was decided to concentrate on the removal of medium-sized orbital debris, that is, those pieces ranging from 1 cm to 50 cm in size. The current design incorporates a transfer vehicle and a netting vehicle to capture the medium-sized debris. The system is based near an operational space station located at 28.5 deg inclination and 400 km altitude. The system uses ground-based tracking to determine the location of a satellite breakup or debris cloud. These data are uploaded to the transfer vehicle, which proceeds to rendezvous with the debris at a lower altitude parking orbit. Next, the netting vehicle is deployed, tracks the targeted debris, and captures it. After expending the available nets, the netting vehicle returns to the transfer vehicle for a new netting module and continues to capture more debris in the target area. Once all the netting modules are expended, the transfer vehicle returns to the space station's orbit where it is resupplied with new netting modules from a space shuttle load. The new modules are launched by the shuttle from the ground and the expended modules are taken back to Earth for removal of the captured debris, refueling, and repacking of the nets. Once the netting modules are refurbished, they are taken back into orbit for reuse. In a typical mission, the system has the ability to capture 50 pieces of orbital debris. One mission will take approximately six months and the system is designed to allow for a 30 deg inclination change on the outgoing and incoming trips of the transfer vehicle.

Source record↗

NASA NTRS1990

Final design of a space debris removal system

The objective is the removal of medium sized orbital debris in low Earth orbits. The design incorporates a transfer vehicle and a netting vehicle to capture the medium size debris. The system is based near an operational space station located at 28.5 degrees inclination and 400 km altitude. The system uses ground based tracking to determine the location of a satellite breakup or debris cloud. This data is unloaded to the transfer vehicle, and the transfer vehicle proceeds to rendezvous with the debris at a lower altitude parking orbit. Next, the netting vehicle is deployed, tracks the targeted debris, and captures it. After expending the available nets, the netting vehicle returns to the transfer vehicle for a new netting module and continues to capture more debris in the target area. Once all the netting modules are expended, the transfer vehicle returns to the space station's orbit, where it is resupplied with new netting modules from a space shuttle load. The new modules are launched by the shuttle from the ground, and the expended modules are taken back to Earth for removal of the captured debris, refueling, and repacking of the nets. Once the netting modules are refurbished, they are taken back into orbit for reuse. In a typical mission, the system has the ability to capture 50 pieces of orbital debris. One mission will take about six months. The system is designed to allow for a 30 degree inclination change on the outgoing and incoming trips of the transfer vehicle.

Carlson, Erika↗

DOE OSTI2020

Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles

The range anxiety has been a major factor that affects the market acceptance of electric vehicles. Even with the recent development of battery technologies, a lack of charging stations and range anxiety are still significant concerns, specifically for intercity trips. This calls for more investments in building charging stations and advancing battery technologies to increase the market share of electric vehicles and improve sustainability. This study suggests a configuration for plug-in electric vehicle charging infrastructure to support long-distance intercity trips of electric vehicles at the network level. A model is proposed to minimize the total system cost including infrastructure investment (building charging stations/spots) and travel time delays (charging time, waiting time in the queue, and detour time to access charging stations). This study fills existing gaps in the literature by capturing realistic patterns of travel demand and considering flow-dependent charging delays at charging stations. Furthermore, the proposed model, which is formulated as a mixed-integer program with nonlinear constraints, solves the optimization problem at the network level. At the network level, impacts of charging station locations on the traffic assignment problem with a mixed fleet of electric and conventional vehicles need to be considered. To this end, a traffic assignment module is integrated with a simulated annealing algorithm. The numerical experiments show a satisfactory application of the model for a full-scale case study (intercity network in Michigan). The solution quality and efficiency of the proposed solution algorithm are evaluated against those of an enumeration approach for a small case study. The results suggest that even for the current market share and charging stations’ setting, a significant investment is needed to support intercity trips without range anxiety issues and with acceptable delays. Additionally, through sensitivity analyses, the required infrastructure and battery investments to support intercity trips with acceptable delays are established for hypothetical increased market shares and battery size in the future.

42 ENGINEERING↗

NASA NTRSDate not supplied

TCCON Station Update for NASA Armstrong Site

The current operational status of the Total Carbon Column Observing Network (TCCON) station located at NASA Armstrong Flight Research Center will be presented. Additionally, we will present initial results from comparisons of the lower column data product with the in-situ validation measurements collected from aircraft.

AIRCRAFT↗