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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Design of a real-time wind turbine simulator using a custom parallel architecture

The design of a new parallel-processing digital simulator is described. The new simulator has been developed specifically for analysis of wind energy systems in real time. The new processor has been named: the Wind Energy System Time-domain simulator, version 3 (WEST-3). Like previous WEST versions, WEST-3 performs many computations in parallel. The modules in WEST-3 are pure digital processors, however. These digital processors can be programmed individually and operated in concert to achieve real-time simulation of wind turbine systems. Because of this programmability, WEST-3 is very much more flexible and general than its two predecessors. The design features of WEST-3 are described to show how the system produces high-speed solutions of nonlinear time-domain equations. WEST-3 has two very fast Computational Units (CU's) that use minicomputer technology plus special architectural features that make them many times faster than a microcomputer. These CU's are needed to perform the complex computations associated with the wind turbine rotor system in real time. The parallel architecture of the CU causes several tasks to be done in each cycle, including an IO operation and the combination of a multiply, add, and store. The WEST-3 simulator can be expanded at any time for additional computational power. This is possible because the CU's interfaced to each other and to other portions of the simulation using special serial buses. These buses can be 'patched' together in essentially any configuration (in a manner very similar to the programming methods used in analog computation) to balance the input/ output requirements. CU's can be added in any number to share a given computational load. This flexible bus feature is very different from many other parallel processors which usually have a throughput limit because of rigid bus architecture.

Hoffman, John A.↗
NASA NTRS2000

Improved Results for Route Planning in Stochastic Transportation Networks

In the bus network problem, the goal is to generate a plan for getting from point X to point Y within a city using buses in the smallest expected time. Because bus arrival times are not determined by a fixed schedule but instead may be random. the problem requires more than standard shortest path techniques. In recent work, Datar and Ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed. We offer solutions to two important generalizations of the problem, answering open questions posed by Datar and Ranade. First, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. This class includes not only exponential distributions but also uniform, normal, and gamma distributions. Second, in the case where bus arrival times are independent and geometric discrete random variable,. we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.

Boyan, Justin↗
NASA NTRS2005

AC/DC Power Systems with Applications for future Lunar/Mars base and Crew Exploration Vehicle

ABSTRACT The Power Systems branch at JSC faces a number of complex issues as it readies itself for the President's initiative on future space exploration beyond low earth orbit. Some of these preliminary issues - those dealing with electric power generation and distribution on board Mars-bound vehicle and that on Lunar and Martian surface may be summarized as follows: Type of prime mover - Because solar power may not be readily available on parts of the Lunar/Mars surface and also during the long duration flight to Mars, the primary source of power will most likely be nuclear power (Uranium fuel rods) with a secondary source of fuel cell (Hydrogen supply). The electric power generation source - With nuclear power being the main prime mover, the electric power generation source will most likely be an ac generator at a yet to be determined frequency. Thus, a critical issue is whether the generator should generate at constant or variable frequency. This will decide what type of generator to use - whether it is a synchronous machine, an asynchronous induction machine or a switched reluctance machine. The type of power distribution system - the distribution frequency, number of wires (3- wire, 4-wire or higher), and ac/dc hybridization. Building redundancy and fault tolerance in the generation and distribution sub-systems so that the system is safe; provides 100% availability to critical loads; continues to operate even with faulted sub-systems; and requires minimal maintenance. This report descril_es results of a summer faculty fellowship spent in the Power Systems Branch with the specific aim of investigating some of the lessons learned in electric power generation and usage from the terrestrial power systems industry, the aerospace industry as well as NASA's on-going missions so as to recommend novel surface and vehicle-based power systems architectures in support of future space exploration initiatives. A hybrid ac/dc architecture with source side and load side redundancies and including emergency generators on both ac and dc sides is proposed. The generation frequency is 400 Hz mostly because of the technology maturity at this frequency in the aerospace industry. Power will be distributed to several ac load distribution buses through solid state variable speed, constant frequency converters on the ac side. A segmented dc ring bus supplied from ac/dc converters and with the capability of connecting/disconnecting the segments will supply power to multiple de load distribution buses. The system will have the capability of reverse flow from dc to ac side in the case of an extreme emergency on the main ac generation side.

Chowdhury, Badrul H.↗
NASA NTRS2006

Providing Housing, Food and Medical Support for 25,000 Katrina Evacuees with 12 Hours Notice: The Harris County Medical Support of the Superdome Evacuees

Hurricane Katrina was responsible for trapping 25,000 people in the New Orleans Superdome and isolating many others throughout Louisiana and Mississippi. The transport of these evacuees to the Reliant Park (Houston, Texas) used 500 buses each containing about 55 people. Processing the arriving evacuees included addressing their health status and medical needs as follows: an initial triage at disembarkation, a secondary triage in the Reliant Astrodome and Center, and definitive clinical care in the Reliant Arena "Katrina" Clinic. Baylor College of Medicine (BCM) physicians boarded buses and identified the sickest for emergency transport to Harris County Hospital District (HCHD) hospitals. BCM departments represented included pediatrics, family and community medicine, internal medicine, radiology, obstetrics and gynecology, orthopedics, surgery, and psychiatry. Astrodome and Center triage was managed by BCM physicians and staffed by HCHD Nurses and volunteers from Texas and beyond. The Reliant Astrodome, Center and Arena reached peak headcounts of 15,000,4500, and 2500, respectively Most evacuees visiting the triage sites in the Astrodome and Center were treated using "over-the-counter" medications with the remaining being transported to the "Katrina" clinic. The clinic was equipped with a lab, pharmacy, digital X-ray, and ultrasound machines in addition to electronic patient records created using 80 computer terminals. The Katrina clinic saw more than 15,000 patients during 15 days of operations (2,000 on the first full day), administered 10,000 tetanus shots, and filled thousands of prescriptions. At the peak of operations, the clinic saw 150 patients/hour with 25 physicians scheduled for each 12-hour shift. Approximately 900 people were transported to hospital emergency rooms. Within 3 weeks of arriving at the Reliant Park facilities, more than 90% of the families found permanent housing, enrolled children in schools, and found work. Using data obtained from manual and electronic medical records, this presentation will document the major milestones and lessons learned from this extraordinary project to help the Katrina evacuees.

Hamilton, Douglas↗
NASA NTRS2012

Use of CCSDS Packets Over SpaceWire to Control Hardware

For the Lunar Reconnaissance Orbiter, the Command and Data Handling subsystem consisted of several electronic hardware assemblies that were connected with SpaceWire serial links. Electronic hardware would be commanded/controlled and telemetry data was obtained using the SpaceWire links. Prior art focused on parallel data buses and other types of serial buses, which were not compatible with the SpaceWire and the core flight executive (CFE) software bus. This innovation applies to anything that utilizes both SpaceWire networks and the CFE software. The CCSDS (Consultative Committee for Space Data Systems) packet contains predetermined values in its payload fields that electronic hardware attached at the terminus of the SpaceWire node would decode, interpret, and execute. The hardware s interpretation of the packet data would enable the hardware to change its state/configuration (command) or generate status (telemetry). The primary purpose is to provide an interface that is compatible with the hardware and the CFE software bus. By specifying the format of the CCSDS packet, it is possible to specify how the resulting hardware is to be built (in terms of digital logic) that results in a hardware design that can be controlled by the CFE software bus in the final application

Haddad, Omar↗
NASA NTRS2015

Characterizing Debris in the Infrared with UKIRT

The United Kingdom Infrared Telescope (UKIRT) has been a major asset for the NASA Orbital Debris Program Office (OPDO) since March, 2014. With the UKIRT current contract coming to an end at the finish of FY15, there is a golden opportunity for this community to fund and gain access to UKIRT as an SSA asset through HCAR (Hawaii Center for Astronautics Research). UKIRT is the only telescope on Mauna Kea dedicated to infrared bands. Spectral coverage ranges from the near- (0.8-5μm) to the mid- to far-infrared (8-25 micrometer) regime. To date, debris observations have been collected with three instruments. Near-Infrared photometry with ZYJHK filters has been obtained with the Wide Field Camera (WFCam). Near-Infrared (1-2.5 micrometer) spectra are the focus of observations taken with the UKIRT Imager SpecTrometer (UIST). And Michelle (Mid Infrared escCHELLE) is a thermal imager-spectrometer designed for the 8-25 micrometer regime. With 35% of the telescope time allocated to ODPO, a very steady stream of data has been collected on a variety of debris targets using all the above instrumentation. Initial results from WFCam were discussed at AMOS and NISOI including analyses on IDCSPs, the MSG cooler and baffle covers. The cylindrical HS-376 buses were the focus of recent WFCam runs. Summary analyses of these works will be presented. Focus will be given to initial results of the data collected with the Cassegrain instruments, UIST and Michelle. UIST spectra were collected in September 2014, March and April 2015. Targets included a suite of HS-376 buses, well suited to investigate the signatures of blue solar panels; several dead satellites with solar array wings; Titan 3C transtage debris; the CTA Array cover, and others. In addition, Michelle mid-IR photometry was collected on a select few objects during the April 2015 run. Using WFCam, UIST and Michelle the Lockheed Martin has been observing operational satellites in the near- mid and far-infrared regime in an attempt to understand the health and status of several satellites that are based on the Lockheed Martin A2100 bus. The potential insights into debris characterization using this range of assets, and early analyses will be discussed, as well as the opportunities possible for utilizing UKIRT as an SSA asset.

Lederer, S. M.↗
NASA NTRS2016

Infrared Studies of the Reflective Properties of Solar Cells and the HS376 Spacecraft

In 2015, a selection of HS-376 buses were observed photometrically with the United Kingdom Infrared Telescope (UKIRT) to explore relationships between time-on-orbit and Near Infrared (NIR) color. These buses were chosen because of their relatively simple shape, for the abundance of similar observable targets, and their surface material being primarily covered by solar cells. While the HS-376 spacecraft were all very similar in design, differences in the specific solar cells used in the construction of each model proved to be an unconstrained variable that could affect the observed reflective properties. In 2016, samples of the solar cells used on various models of HS-376 spacecraft were obtained from Boeing and were analyzed in the Optical Measurements Center at the Johnson Space Center using a visible-near infrared field spectrometer. The laboratory-based spectra are convolved to match the photometric bands previously obtained using UKIRT and compared with the on-orbit photometry. The results and future work are discussed here.

Frith, James↗
NASA NTRS2019

Program Management for Concurrent University Satellite Programs, Including Propellant Feed System Design Elements

Propulsion options for CubeSats are limited but are necessary for the CubeSat industry to continue future growth. Challenges to CubeSat propulsion include volume/mass constraints, availability of sufficiently small and certified hardware, secondary payload status, safe storage of high energy, and power requirements. A multi-mode (chemical and electric) thruster was developed by at the Missouri University of Science and Technology (Missouri S&T) to enable CubeSat propulsion missions. Two satellite buses, a 3U and 6U, are being developed by the M-SAT satellite research team at Missouri S&T to demonstrate the multi-mode thruster's capabilities. Two key challenges related to these missions are the development of the feed system to support the thruster and management of the two programs' personnel, resources, timelines, and budgets. The feed system was designed to support the unique needs of the thruster including material compatibility with the custom ionic liquid, variable flow rate, high pressurization, and high voltage within the constraints and budget of a student-designed propulsion system. The feed system was also designed to minimize risk as a secondary payload. This resulted in the development of a unique method to pressurize propellant stored in the feed system tubing. Within the expected operating pressure range, the method was experimentally shown to provide sufficient pressure and propellant volume to the thruster to meet mission success criteria. The 3U and 6U CubeSat buses were designed concurrently with complimentary payloads, hardware, objectives, and team structures. Resources such as personnel, lab space, and time had to be carefully balanced between the two teams. With proper management, the two programs have been able to support one another, providing valuable insight and collaboration between the two teams. Lessons learned include experience with design, testing, and assembly of hardware, team training/mentoring and motivation, improved documentation practices, and risk management.

Withrow, Shannah Nichole↗
NASA NTRS2022

Gaussian Process Regression Method for Costing SmallSat Bus Capabilities

NASA is responding to the growing interest in, andcapabilities of, small satellites for science applications with an increasingnumber and frequency of Announcements of Opportunityfor small satellite space missions. Estimating the probabilitythat these mission concepts will fit within the small cost capsof these opportunities is largely driven by the probability thatone of the burgeoning number of small satellite providers will beable to meet the payload’s accommodation requirements withinthe budget for the spacecraft. JPL has collected a databasecontaining technical specifications and cost of commerciallyavailable Smallsat buses across various vendors. The primarypurpose of the database is for use in JPL’s Team X architecturestudies to inform cost estimates of a spacecraft bus which fitsthe customer’s technical requirements for their payload andmission. Customer needs are often unique and don’t alignperfectly with an off-the-shelf commercial spacecraft bus, whichmotivates the need to develop a cost model across the continuoustechnical parameter space.Al’s Bus Cost Distribution Estimator (ABCDE) uses Gaussianprocess regression (GPR) to predict commercial Smallsat spacecraftbus cost based on a subset of a customer’s technicalrequirements (payload mass, payload power, delta V, pointingcontrol, and downlink rate). GPR is implemented in ABCDE asa Bayesian method which fits an implied multivariate regressionon the technical parameters and uses kriging to intentionally“overfit” the residuals. Overfitting the residuals allows costestimates to collapse in uncertainty closer to the data pointswhile maintaining larger uncertainty intervals in regions of parameterspace with fewer data records. The data used to fit thismodel is sensitive and represents cost estimates for off-the-shelfcommercial buses. GPR simultaneously protects the sensitivityof the database and uses the sparse nature of the database toaccount for uncertainty in cost in a useful way. For a givenset of customer technical requirements, the tool provides a costestimate distribution, the percentiles of which can be interpretedas a confidence level of finding a commercial bus under a specifiedcost cap. ABCDE dramatically pushes the boundaries ofspacecraft cost estimation models due to its Bayesian methodology(accounting for the maximum uncertainty in the underlyingregression), the mathematically advanced kriging methodology,and the novelty of its application in Team X architecture tradestudies.

Austin, Alex↗
DOE OSTI2020

Vehicle Platooning: An Energy Consumption Perspective

Urban traffic congestion is a chronic problem faced by many cities in the US and worldwide. It results in inefficient infrastructure use as well as increased vehicle fuel consumption and emission levels. Excessive fuel consumptions add extra costs to commuters as well as transportation businesses. Consuming less fuel and thus reducing costs by a single percentage digit can have a significant impact on the balance sheet as well as the protection of the environment. Researchers have developed, and continue to develop, tools and systems to optimize the operations of fleets as well as engines in order to burn less fuel and therefore generate less CO2 emissions. Platooning is one such tool that attempts to maintain relatively small distances (i.e. pre-determined time gap) between consecutive vehicles. It has the potential to increase the capacity of the road as well as reduce the consumed fuel. In this paper, we use a fuel consumption model for internal combustion light-duty vehicles, electric vehicles, hybrid electric vehicles, buses and trucks in order to determine and quantify the effects of platooning on a fleet fuel consumption. The results suggest that a reduction of up to 3%, 3.5%, 4.5 %, 10%, and 15% in fuel consumption can be achieved for internal combustion engine vehicles, hybrid electric vehicles, electric vehicles, buses and trucks.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Propane Basics

Propane powers nearly 60,000 vehicles in the United States. Fleets around the United States have successfully implemented propane vehicles in many types of applications, including school buses, shuttle buses, step vans, and law enforcement vehicles. Propane is also frequently used in off-road applications, such as forklifts, commercial landscape mowers and equipment, and other farm equipment. The advantages of propane include its domestic availability, performance, and emissions benefits.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗
DOE OSTI2020

Demand-adaptive Transit Design for Urban Transportation Hubs

In this study, we proposed a novel three-stage framework for planning the optimal demand-adaptive transit (DAT) at urban transportation hubs. Given the potential trip demand and road traffic condition, the proposed framework sequentially generates the optimal set of candidate routes, combines the outgoing routes and incoming routes at the hub, and derives the optimal fleet size and corresponding route frequency under the fixed budget. In particular, we build the route generation algorithm which maximizes passenger demand coverage with travel time deviation constraint. And a heuristic algorithm is further developed which yields near-optimal operation routes for real-time demand. The fleet optimization problem is formulated to minimize the weighted cost of energy savings, operation cost and trip revenue. We conduct comprehensive numerical experiments for planning DAT with electric buses at JFK airport in NYC using NYC taxi and for-hire vehicle trip data and GoogleMap speed data. The results show the superior performance of the proposed route generation algorithm which is able to cover citywide passenger demand with only 61 DAT routes. The results also suggest that the proposed DAT planning framework may serve over 47% of existing taxi and FHV demand by operating 18 routes using the fleet of 62 electric buses.

demand adaptive↗
DOE OSTI2026

Cold Weather Impacts on Electric School Bus Performance in Aurora, Colorado

This brief highlight details the key takeaways from a project that utilized NLR's Fleet Research, Energy Data, and Insights (FleetREDI) data analysis pipeline related to electric school bus (ESB) operation. ESBs using battery energy as their primary heating source have a higher energy consumption rate in cold weather, which fleet managers can account for when planning ESB purchases and making dispatching and charging decisions. Researchers found that electric school buses operate 2-5 times more efficiently than conventional buses, on average. Cold weather can double electric school bus energy demands, but strategies such as thermal pre-conditioning significantly reduce this effect. Understanding these impacts can help fleets plan charging, dispatching, and purchase decisions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Time-Dependent Electric Bus and Charging Station Deployment Problem

Battery electric buses (BEBs) have gained popularity due to their emission-free and energy-efficient features. Many transit authorities worldwide have set goals to gradually replace their bus fleets with BEBs. Considering the potential decline in BEB battery and charger prices, this study proposes a time-dependent bus fleet transition model to determine the optimal bus fleet transition plan, which includes selecting the bus lines to be electrified, determining the timing and type of BEBs to be purchased, and deploying on-route fast chargers and depot chargers. The model is a bi-objective integer linear program that considers the trade-off between electrified transit mileages and bus electrification costs. A normalized normal constraint method is applied to solve the bi-objective optimization model. The effectiveness of the proposed model is tested using a real-world bus network. Additionally, sensitivity analyses are conducted to better understand the impact of different parameter values on the optimal solutions. Our proposed model can provide transit authorities with a powerful tool to make informed decisions about their BEB fleet replacement plans.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Integrated charging infrastructure planning and charging scheduling for battery electric bus systems

We report studies on the electric bus system planning problem have typically focused exclusively on either the deployment of charging infrastructure or the scheduling of charging events; few have examined the impact of charging facility deployment on charging activities. Considering the interdependence of system design and operational strategies, this study proposes a two-phase optimization framework for charging infrastructure planning and charging scheduling for battery electric bus systems. An integrated optimization model is first developed to simultaneously optimize charger deployment, on-board battery capacity, and charging schedules. A charging scheduling model is further proposed and a rolling horizon approach is utilized in the second phase to optimize the real-time charging scheduling of electric buses. Compared to existing electric bus system planning methods, the proposed integrated model can reduce the total system cost by 19.5%. In addition, compared to uncontrolled charging, the proposed rolling horizon-based charging strategy can reduce the total charging cost by 68.3%.

25 ENERGY STORAGE↗
DOE OSTI2023

Riders’ perceptions towards transit bus electrification: Evidence from Salt Lake City, Utah

While battery electric buses (BEBs) can lead to energy savings and reduced emissions, BEB adoption is developing slowly. Although BEBs offer quieter operations, better acceleration, and no smell of diesel or gas fumes, little focus has been placed on the user’s perspective. Here, this study investigates bus riders’ preferences toward BEBs. To achieve these objectives, a survey was designed and administered to solicit riders’ typical travel behaviors and patterns as well as preferences and opinions about BEBs’ performance in terms of emissions and noise. Statistical analysis showed that several factors influence rider perceptions towards transit bus electrification that include trip purpose, attitudes towards environmental issues and environmental impacts of BEBs, and certain non-instrumental ride factors such as ride comfort and social image. A better understanding of the importance of electrification to transit riders can help transit service providers adjust their marketing decisions and their systemwide operations to accommodate preferences towards BEBs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Joint optimization of electric bus charging infrastructure, vehicle scheduling, and charging management

High upfront costs of vehicles and charging infrastructure as well as the lack of knowledge related to infrastructure planning and electric bus system operation are major obstacles to the implementation of battery electric buses (BEBs). To tackle the obstacles and promote BEB adoption, a comprehensive optimization framework was developed to address the combined charging infrastructure planning, vehicle scheduling, and charging management problem for BEB systems, with the goal to minimize the total cost of ownership. The problem was formulated as a mixed-integer non-linear problem. A genetic algorithm-based approach was then proposed to solve the problem. Last, three alternative scenarios based on a sub-transit network in Salt Lake City, Utah, were analyzed and compared with the optimal scenario results in the numerical experiments. Our comparison results demonstrate the effectiveness of the proposed model and solution algorithm in determining a cost-efficient planning strategy for BEB systems.

33 ADVANCED PROPULSION SYSTEMS↗