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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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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Comprehensive Total Cost of Ownership Quantification for Vehicles with Different Size Classes and Powertrains

In order to accurately compare the costs of two vehicles, the total cost of ownership (TCO) should consist of all costs related to both purchasing and operating the vehicle. This TCO analysis builds on previous work to provide a comprehensive perspective of all relevant vehicle costs of ownership. In this report, we present what we believe to be the most comprehensive explicit financial analysis of the costs that will be incurred by a vehicle owner. This study considers vehicle cost and depreciation, financing, fuel costs, insurance costs, maintenance and repair costs, taxes and fees, and other operational costs to formulate a holistic total cost of ownership and operation of multiple different vehicles. For each of these cost parameters that together constitute a comprehensive TCO, extensive literature review and data analysis were performed to find representative values in order to build a holistic TCO for vehicles of all size classes. The light- and heavy-duty vehicles selected for analysis in this report are representative of those that are on the road today and expected to be available in the future. Important additive analyses in this study include systematic analysis of vehicle depreciation, in-depth examination of insurance premium costs, comprehensive maintenance and repair estimates, analysis of all relevant taxes and fees, and considerations of specific costs applicable to commercial vehicles. We find that cars depreciate faster than light trucks and that older plug-in electric vehicles have a greater depreciation rate than newer electric vehicles. Light-duty vehicle (LDV) insurance costs show comparable costs for different powertrains, and lower costs for larger size classes. Medium- and heavy-duty vehicle (MHDV) insurance costs vary significantly by vocation. Electric and electrified powertrains have lower maintenance and repair costs than internal combustion engine (ICE) powertrains for all vehicle sizes, relative to vehicle price. MHDV maintenance and repair costs depend heavily on vocation and duty cycle. LDV taxes and fees are comparable across powertrain types and size classes, though marginally higher registration fees exist for alternative fuel vehicles. MHDV fees depend on the vocation, weight rating, and state. Many electric tractor trailers would be affected by additional battery weight, reducing the available payload capacity, and this cost can be substantial. Electric vehicle charging for commercial vehicles can be time-consuming; labor rates can cause this cost to dominate TCO. With improved knowledge of each of the cost components, we calculate a lifetime TCO for comparison across vehicles of different types and attributes. For a simulated small sport utility vehicle in 2025, modeled using Autonomie, the hybrid electric vehicle (HEV) has the lowest cost, followed by the conventional ICE vehicle. For MHDV, TCO can be drastically different depending on the vocation. Long-haul vehicles typically have the lowest per-mile costs. Excluding labor costs, the class 4 delivery has a comparable TCO to the day cab. Vocational trucks, refuse trucks, and transit buses have a high per-mile cost of ownership due to maintenance and insurance. For all of these vehicles, the cost of operating the vehicle is heavily weighted by the labor of the driver, followed by the fuel costs. While the HEV begins as the lowest cost powertrain for passenger vehicles, fuel cells are forecast to reach cost parity by 2030 when hydrogen prices reach $\$ 5$/kg while battery electric vehicles (BEV) reach cost parity by 2035 at a battery cost of $\$ 98$ per usable kWh of capacity, with these two technologies being the lowest cost in 2050. For the class 8 day cab tractor, the HEV and ICE vehicle begin as the lowest cost powertrains, and the 250-mile BEV reduces in cost from the most expensive to the least expensive by 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2011

An Analysis of Database Replication Technologies with Regard to Deep Space Network Application Requirements

The Deep Space Network (DSN) has three communication facilities which handle telemetry, commands, and other data relating to spacecraft missions. The network requires these three sites to share data with each other and with the Jet Propulsion Laboratory for processing and distribution. Many database management systems have replication capabilities built in, which means that data updates made at one location will be automatically propagated to other locations. This project examines multiple replication solutions, looking for stability, automation, flexibility, performance, and cost. After comparing these features, Oracle Streams is chosen for closer analysis. Two Streams environments are configured - one with a Master/Slave architecture, in which a single server is the source for all data updates, and the second with a Multi-Master architecture, in which updates originating from any of the servers will be propagated to all of the others. These environments are tested for data type support, conflict resolution, performance, changes to the data structure, and behavior during and after network or server outages. Through this experimentation, it is determined which requirements of the DSN can be met by Oracle Streams and which cannot.

Oracle Database File System↗

DOE OSTI2020

Deep Reinforcement Learning for Residential HVAC Control with Consideration of Human Occupancy

The Artificial Intelligence (AI) development described herein uses model-free Deep Reinforcement Learning (DRL) to minimize energy cost during residential heating, ventilation, and air conditioning (HVAC) operation. Building cooling loads and HVAC operation are difficult to accurately model due to complexity, lack of measurements and data, and model specific performance, so online machine learning is used to allow for real-time readjustment in performance. Energy costs for the multi-zone cooling unit shown in this work are minimized by scheduling on/off commands around dynamic prices. By taking advantage of precooling events that take place when the price is low, the agent is able to reduce operational cost without violating user comfort. The DRL controller was tested in simulation where the learner achieved a 43.89% cost reduction when compared to traditional, fixed-setpoint operation. The system is now ready for the next phase of testing in a live, real-time home environment.

Mckee, Evan↗

NASA NTRS1996

Evolving Requirements for Magnetic Tape Data Storage Systems

Magnetic tape data storage systems have evolved in an environment where the major applications have been back-up/restore, disaster recovery, and long term archive. Coincident with the rapidly improving price-performance of disk storage systems, the prime requirements for tape storage systems have remained: (1) low cost per MB, (2) a data rate balanced to the remaining system components. Little emphasis was given to configuring the technology components to optimize retrieval of the stored data. Emerging new applications such as network attached high speed memory (HSM), and digital libraries, place additional emphasis and requirements on the retrieval of the stored data. It is therefore desirable to consider the system to be defined both by STorage And Retrieval System (STARS) requirements. It is possible to provide comparative performance analysis of different STARS by incorporating parameters related to (1) device characteristics, and (2) application characteristics in combination with queuing theory analysis. Results of these analyses are presented here in the form of response time as a function of system configuration for two different types of devices and for a variety of applications.

Gniewek, John J.↗

DOE OSTI2025

Data Structure Alchemy

In an increasingly more data-driven world, the project set out to uncover the first principles of data-structure design, chart the immense design space they form, and build automation that can synthesize an optimal structure, or even a whole storage engine, for any given workload, hardware platform, and cost target. Data structures are at the center of every computational system and are directly responsible for its performance. Two core technical thrusts were defined: 1) Mapping design spaces for key data-centric abstractions (filters, hash functions, storage-engine layouts, neural-network topologies, blockchain protocols, image layouts, etc.). 2) Developing search & synthesis algorithms, initially analytical cost models, later neural-guided bi-level optimisers that navigate sextillions of candidate designs in seconds and materialise the best one as ready‐to-run code. This report distills the key insights, accomplishments, and impact.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2004

Modular Wireless Data-Acquisition and Control System

A modular wireless data-acquisition and control system, now in operation at Kennedy Space Center, offers high performance at relatively low cost. The system includes a central station and a finite number of remote stations that communicate with each other through low-power radio frequency (RF) links. Designed to satisfy stringent requirements for reliability, integrity of data, and low power consumption, this system could be reproduced and adapted to use in a broad range of settings.

Perotti, Jose↗

DOE OSTI2025

Comparative Economic Analysis Between Bioenergy and Forage Types of Switchgrass for Sustainable Biofuel Feedstock Production: A Data Envelopment Analysis and Cost–Benefit Analysis Approach

ABSTRACT The capacity to produce switchgrass efficiently and cost‐effectively across diverse environments can be pivotal in achieving the short‐ and medium‐term Sustainable Aviation Fuel targets set by the U.S. Department of Energy. This study evaluated the economic performance of forage‐ and bioenergy‐type switchgrass cultivars and their response to N fertilization under diverse marginal environments across the US Midwest that included Illinois (IL), Iowa (IA), Nebraska (NE), and South Dakota (SD). Data Envelopment Analysis (DEA) was used to evaluate the efficiency of 23 Decision‐Making Units (DMUs)—cultivar types and N fertilization rate combinations—while a cost–benefit analysis calculated their profitability over 5 years. Results showed that two energy‐type cultivars—“Independence” and “Liberty”—were superior economically to the forage cultivars. Independence performed best with the highest profit margin when fertilized at 56 kg N ha −1 , particularly in the US hardiness zone 6a (Urbana, IL). Liberty exhibited the highest profit margins in hardiness zone 5b (Madrid, IA, and Ithaca, NE) at 56 kg N ha −1 and showed exceptional profitability with 28 kg N ha −1 in hardiness zone 6b (Brighton, IL). Switchgrass cultivar “Carthage” showed better efficiency score and profitability results in hardiness zone 4b (South Shore, SD) at 56 kg N ha −1 . The profit trends observed in current study sites may indicate broader patterns across similar US hardiness zones. This study provides valuable insights for decision‐makers to optimize input strategies for biomass production of bioenergy switchgrass to meet renewable energy demands.

Arshad, Muhammad Umer [Department of Crop Sciences↗

DOE OSTI2024

An Effective Earned Value Management System (EVMS) is a Team Sport

We present a novel framework to assess 27 earned value management system (EVMS) environment factors and investigate their impact on project performance. A study of the EVMS literature, a survey of practitioners, and focus group meetings with 36 EVMS industry and government experts, supported the development of the framework. Focus groups involving 80 practitioners refined and tested it. We analyzed performance data from 35 completed projects/programs representing over US$21.8 billion in total cost; a project demonstrating a positive environment could save up to 25% in cost versus baseline. Practitioners can develop an effective EVMS environment by following the provided guidance.

Aramali, Vartenie↗

DOE OSTI2026

Offshore Wind Farm Turbine and Energy Storage Optimization

Abstract This paper evaluates the technical and economic feasibility of repurposing decommissioned offshore oil and gas platforms as electrical substations for offshore wind projects in the U.S. Gulf of America, a region characterized by relatively low and highly variable wind speeds, extensive legacy offshore infrastructure, and exposure to merchant electricity markets. A unified techno-economic framework is developed using the Repurposing Offshore Infrastructure for Continued Energy (ROICE) Economic Model (REM) to integrate Gulfspecific wind resource assessment, commercial wind turbine performance, offshore infrastructure cost modeling, and wholesale electricity market exposure. Gulf wind speed data are vertically extrapolated to turbine hub height and combined with manufacturer power curves to compute annual energy production and capacity factors across a broad portfolio of commercial turbines, enabling identification of turbine designs best suited for low-wind offshore environments. Hourly electricity price data from the Midcontinent Independent System Operator (MISO) day-ahead market are incorporated to characterize revenue potential, price volatility, and the temporal alignment between wind generation and market conditions. In addition, a conceptual framework for offshore battery energy storage system (BESS) integration is developed to support future investigation of market-responsive energy shifting at repurposed platforms. Results from the turbine evaluation demonstrate that machines with lower cut-in wind speeds and earlier ‘rated-power’ characteristics significantly outperform larger, industry-standard offshore turbines for the same net power under Gulf wind conditions, underscoring the need for region-specific technology selection. Market analysis further reveals substantial price variability and limited intrinsic alignment between wind production and high-price periods, motivating consideration of operational flexibility mechanisms. While storage optimization is not implemented in this study, the REM framework establishes a transparent and replicable foundation for co-evaluating turbine selection, infrastructure constraints, and market exposure, providing a practical pathway for assessing the potential role of repurposed offshore platforms in enabling economically viable offshore wind development in the Gulf of America.

02 PETROLEUM↗

NASA NTRS1974

Multispectral scanner data applications evaluation. Volume 2: Sensor system study

The optimization of a thematic mapper for earth resources application is discussed in terms of cost versus performance. Performance tradeoffs and the cost impact are analyzed. The instrument design and radiometric performance are also described. The feasibility of a radiative cooler design for a scanning spectral radiometer is evaluated along with the charge coupled multiplex operation. Criteria for balancing the cost and complexity of data acquisition instruments against the requirements of the user, and a pushbroom scanner version of the thematic mapper are presented.

Source record↗

NASA NTRS1976

An inexpensive economical solar heating system for homes

A low-cost solar home heating system to supplement existing warm-air heating systems is described. The report is written in three parts: (1) a brief background on solar heating, (2) experience with a demonstration system, and (3) information for the homeowner who wishes to construct such a system. Instructions are given for a solar heating installation in which the homeowner supplies all labor necessary to install off-the-shelf components estimated to cost $2,000. These components, which include solar collector, heat exchanger, water pump, storage tank, piping, and controls to make the system completely automatic, are available at local lumber yards, hardware stores, and plumbing supply stores, and are relatively simple to install. Manufacturers and prices of each component used and a rough cost analysis based on these prices are included. This report also gives performance data obtained from a demonstration system which was built and tested at the Langley Research Center.

Allred, J. W.↗

NASA NTRS2013

On the Performance Potential of Bioelectrochemical Life Support Systems

An area of growing multi-disciplinary research and revolutionary development for bio-processing on Earth is bioelectrochemical systems. These systems exploit the capability of many microorganisms to act as biocatalysts, enhancing the performance of electrochemical processes which convert low-value materials into valuable products. Many varieties of such processes hold potential value for space exploration as means to recycle metabolic waste and other undesirable materials or insitu resources into oxygen, water, and other valuable substances. However, the wide range of possible reactants, products, configurations, and operating parameters, along with the early stage of development and application on the ground necessitate thorough consideration of which, if any, possibilities could outperform existing technologies and should thus receive investment for space applications. In turn, the decision depends on the theoretical and practical limits of performance and the value of the reactant-product conversions within spaceflight scenarios, and should, to the greatest extent possible, be examined from the perspective of a fully designed, integrated system, rather than as an isolated unit lacking critical components like valves and pumps. Herein, we select a series of possible reactant-product conversions, develop concept process flow diagrams for each, and estimate theoretical and (where sufficient literature data allows) practical performance limitations of each. The objective was to estimate the costs, benefits, and risks of each concept in order to aid strategic decisions in the early-phase technology development effort.

Mansell, J. Matthew↗

NASA NTRS2019

NASA SIERRA-B Capability Returns to Flight

The Sensor Integrated Evaluation Remote Research Aircraft (SIERRA-B) is a medium-class, unmanned aircraft system (UAS) that can perform remote sensing and atmospheric sampling missions in isolated and often inaccessible regions, such as over mountain ranges, the open ocean, or the Arctic. This capability developed by NASA Ames Research Center is a unique way for Scientists and Engineers to gather important Earth science data as well as perform flight research using an innovative, safe, and cost-effective aerial platform. This poster describes the aircraft system architecture, capabilities, and provides an overview of current payloads and mission concepts.

Cahill, S.↗

NASA NTRS2018

Smartphone scene generator for efficient characterization of visible imaging detectors

Full characterization of imaging detectors involves subjecting them to spatially and temporally varying illumination patterns over a large dynamic range. Here we present a scene generator that fulﬁlls many of these functions. Based on a modern smartphone, it has a number of good features, including high spatial resolution (13 um), high dynamic range (∼104), near-Poisson limited illumination stability over time periods from 100 ms to many days, and no background noise. The system does not require any moving parts and may be constructed at modest cost. We present the optical, mechanical, and software design, test data validating the performance, and application examples.

Demers, Richard T.↗

NASA NTRS2018

Ka-band High-Rate Downlink System for the NISAR Mission

This paper provides a description and analyses of the high-rate Ka-band telecom system for the upcoming NISAR (NASA-ISRO Synthetic Aperture Radar) mission. NISAR is a collaborative Earth-Science mission between National Aeronautics and Space Administration (NASA) and Indian Space Research Organization (ISRO), which features an L-band SAR instrument and an S-band SAR instrument. The simultaneous dual-frequency radar system at peak rates will produce data at gigabit-per-second speeds, which drives the data-volume requirements. The key driving requirement for the payload communication subsystem is to provide a minimum of 26 Terabits per day of radar science data to the ground. The high-rate transmitter on the flight system is a software-defined radio developed at the Jet Propulsion Laboratory (JPL), based on the Universal Space Transponder platform, providing an offset quadrature phase shift key modulated waveform with Low-Density Parity-Check encoding of the data transfer frames. Two transmitters used in a dual-polarization configuration with each transmitter providing two giga-symbols per second (Gsps) of coded data provides an aggregate rate of four Gsps. In this system, only one watt of signal power is necessary on each polarization to overcome propagation losses and achieve a successful RF link. Several Near Earth Network (NEN) ground station sites (Alaska in the United States, Svalbard in Norway, and Punta Arenas in Chile) are baselined for the space-to-Earth communications link. Each ground station will also feature multiple upgrades to support NISAR’s transmission starting with new Ka-band antennas, wideband downconverters and high-rate receivers. In addition, a baseband data processor called Data Acquisition Processor and Handling Network Environment (DAPHNE), newly developed by the NEN, provides data storage and connectivity to backhaul networks. With NISAR’s large quantities of data (over 3.5 Petabytes over the mission), the processing of science data will be primarily performed on a cloud system to reduce the overall cost to the mission. The system described herein will be the first operational use of Gsps-class downlink rates on an Earth-Science mission.

Dissanayake, Asoka↗

NASA NTRS2025

Influence of Actuator Movement Rate During Acquisition of Inlet Characterization Data

This report considers using a process to acquire performance data for supersonic mixed-compression inlets that is faster and less costly than the previous process. In the previous process for acquiring data during wind tunnel experiments, actuators for backpressuring an inlet moved in discrete increments, paused for dynamics to dampen, measured data for 5 s, recorded the data, and then reduced the data to graphic plots of pressure recovery versus mass capture ratio. This discrete data acquisition procedure was methodical, reliable, and accurate. However, acquiring data to characterize the inlet consumed significant wind-on time. Wind tunnel operation was costly when considering maintenance, energy, and human resources (operators and research team); therefore, the price for each data point was high. This report presents a quicker method to obtain all measurements, one which can also be used in blowdown wind tunnels. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. The backpressuring actuator moves continuously, and measurements from high-speed pressure sensors are recorded as the actuator progresses to and past the incremental points. Despite its advantages, the approach raised the following questions: (1) Will the new process be as accurate as the previous process? and (2) Are there any hidden costs? These concerns are addressed in this report. This report reviews a study that was undertaken to compare wind tunnel experiment data taken using the previous discrete data acquisition procedure with data recorded using the dynamic inlet characterization data acquisition procedure. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data for analysis are explained, and a discussion of the results is given. Finally, conclusions from this study that may guide further work in this area are presented.

Inlet Characterization Curves↗

NASA NTRSDate not supplied

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Inlet↗

NASA NTRSDate not supplied

An Efficient Approach to Collect Inlet Characterization Data

Data Acquisition↗