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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps

In this project, we developed a techno-economic analysis (TEA) model that can be used to evaluate the viability of a proposed Geological Thermal Energy Storage (GeoTES) design. This MATLAB-based model integrates distinct subsystem models for the reservoir, wells, power cycle, and solar field to capture their distinct characteristics. It applies this approach in simulating GeoTES storage and dispatch operations for durations ranging from hourly to seasonal. Using cases studies based on GeoTES designs provided by industry partners - Premier Resource Management (PRM) and EarthBridge Energy - we validated the TEA model estimations of system performance and costs (such as thermal and electrical power/energy inflow and outflow, capital costs, and levelized costs of energy and storage) for both concentrating solar thermal (CST) and Carnot Battery (CB) pairings with GeoTES (CST-GeoTES and CB-GeoTES). For the CST-GeoTES case, the model was validated against the proposed system designed by PRM. It showed good agreement with PRM's estimations when well and pump costs derived from PRM's estimations were used. When GETEM-based costs were used, there was a slight overprediction due to GETEM's project/site agnostic assumption of these costs. From a sensitivity analysis perspective, the levelized cost of electricity (LCOE) of the CST-GeoTES case was most sensitive to well flow rate and the charging temperature. An optimal design scenario resulted in an LCOE of 0.11 $\$$/kWhe. CST-GeoTES can also provide a source of heat to meet seasonal demands. With 12-hour and 24-hour levelized cost of heat (LCOH) of 0.018 $\$$/kWhth and 0.022 $\$$/kWhth, respectively, CST-GeoTES could be competitive in the California market with an average industrial price of natural gas in California between 0.041-0.047 $\$$/kWhth. The levelized cost of storage (LCOS) for CST-GeoTES depends on the energy storage duration. Although the LCOS is relatively higher for shorter durations (e.g., ~0.50 $\$$/kWhe for 1 hour of storage), it is an order of magnitude lower (0.06 $\$$/kWhe) for longer storage durations and competitive with lithium-ion batteries (beyond 12 hours of storage) and molten-salt thermal energy storage (beyond 32 hours). Energy. Three options were explored and applied to the EarthBridge case study: (1) A Carnot Battery design using R125 working fluid with both hot and cold storage; (2) A Carnot Battery design using R125 working fluid with only hot storage; (3) A Carnot Battery using a commercially available heat pump with carbon dioxide (CO2) working fluid and hot storage only. The CB-GeoTES with cold storage only had a slight (round-trip) efficiency advantage over the system without (43.4% vs. 42.8%). This is because the cold storage is limited by the freezing point of water, so the cold storage is not much colder than the environment. The system using commercially available technologies was the least efficient - partly because different cycles were used in the heat pump (CO2) and heat engine (binary cycle) which leads to some inefficiencies. Using the commercially available design, the levelized cost of energy (LCOS) from the model (0.10 $\$$/kWhe) was higher than that estimated by EarthBridge (0.068 $\$$/kWhe). This is because of the low round-trip (38.7%) efficiency of the commercially available design. Sensitivity analysis reveals that the model is most sensitive to electricity price. Including electricity price in the TEA for CB-GeoTES leads to an increase in LCOS from the base value to 0.25 $\$$/kWhe. To determine storage sites suitable for GeoTES, we gathered and analyzed geological, petrophysical, and geophysical data of oil and gas reservoir and aquifers in California and Texas. We down-selected possible sites based on cut-off values for site characteristics (e.g., reservoir temperature, formation thickness, permeability, porosity, depth, and brine salinity) and preliminary costs. Using this approach, the Carrizo-Wilcox, Yegua-Jackson, and Dockum brackish aquifers in Texas were identified as having the highest suitability. Similarly, in the central California region, the White Wolf, Belridge South Tulare, and Belridge South Reef Ridge were the most suitable. Going further, we assessed the storage potential in the selected sites. To do this we developed distributions of reservoir characteristic data and applied a Monte Carlo-based analysis to account for intrinsic uncertainty in the acquired data. The analysis revealed that the Carrizo-Wilcox aquifer had the highest storage potential with a mean capacity of 554 TWhth (i.e., 63 TWhe). The estimated capacity serves as an upper limit of storage potential given that not all fields in the basin will be developed. We participated in multiple outreach activities including conference presentations, panel session discussions, and the facilitation of a GeoTES workshop at the NREL Golden campus.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

A multiscale cohesive law for carbon fiber networks

Better predictive models of mechanical failure in low-weight heat shield composites would aid material certification for missions with aggressive atmospheric entry conditions. In this study, we develop such a model for the rapid engineering analysis of the failure limits of phenolic impregnated carbon ablator (PICA) - a leading heat shield material whose structural component is a carbon fiber network. We hypothesize inelastic deformation failure mechanisms and model their behavior using molecular dynamics simulations to calculate the binding energy. We then upscale this binding energy to the macroscale using a renormalization argument. The approach delivers insightful and reasonably accurate macroscale predictions that compare favorably to experiments. In application, the model is validated for a particular variety of PICA by comparison to experiment and would then be used to study design scenarios in different entry conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The Implications of Global Change for the Co-Evolution of Argentina's Integrated Energy-Water-Land Systems

This study seeks to understand how Argentina’s energy, water, and land (EWL) systems will co-evolve under a representative array of human and earth system influences, including socioeconomic change, climate change, and climate policy. To capture Argentina’s sub-national EWL dynamics in the context of global change, we couple the Global Change Analysis Model with a suite of consistent, gridded sectoral downscaling models to explore multiple stakeholder-engaged scenarios. Across scenarios, Argentina has the economic opportunity to use its vast land resources to satisfy growing domestic and international demand for crops, such as oil (e.g., soy) and biomass. The human (rather than earth) system produces the most dominant changes in mid-century EWL resource use. A Reference scenario characterized by modest socioeconomic growth projects a 40% increase in Argentina’s agricultural production by 2050 (relative to 2020) by using 50,000 km 2 of additional cropland and 40% more water. A Climate Policy scenario designed to achieve net-zero carbon emissions globally shortly after mid-century projects that Argentina could use 100,000 km 2 of additional land (and 65% more water) to grow biomass and other crops. The burden of navigating these national opportunities and challenges could fall disproportionately on a subset of Argentina’s river basins. The Colorado and Negro basins could experience moderate-to-severe water scarcity as they simultaneously navigate substantial irrigated crop demand growth and climate-induced declines in natural water availability. Argentina serves as a generalizable testbed to demonstrate that multi-scale EWL planning challenges can be identified and managed more effectively via integrated analysis of coupled human-earth systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Comparison of Current and Future PM2.5 Air Quality in China Under CMIP6 and DPEC Emission Scenarios

The latest scenarios for the sixth Coupled Model Intercomparison Project (CMIP6) provide opportunities to explore future climate and air pollution mitigation pathways with socioeconomic features. However, to what extent inadequate consideration of region-specific policies in the CMIP6 scenarios would affect regional air quality projections is still not clear. Here, we simulated China’s future PM2.5 concentrations and compositions with local policy-based scenarios and the original CMIP6 datasets, for the first time estimating future air quality differences induced by the lack of local pollution control policies in the CMIP6 scenarios. We found that the CMIP6-driven projections overestimate major chemical aerosols by 10% – 70% in 2015 and fail to capture the rapid PM2.5 concentration decline during 2015–2019. Near-term differences further lead to 43% – 49% (5 – 9 µg/m3) PM2.5 overpredictions in 2050 in CMIP6 scenarios compared with policy-based mitigation scenarios. Our study demonstrates the indispensable influences of local policies on regional analyses and suggests that the research community should incorporate more region-specific information in future scenario designs.

Cheng, Jing↗
DOE OSTI2024

Feasibility of peak temperature targets in light of institutional constraints

Despite faster-than-expected progress in clean energy technology deployment, global annual CO 2 emissions have increased from 2020 to 2023. The feasibility of limiting warming to 1.5 °C is therefore questioned. Here we present a model intercomparison study that accounts for emissions trends until 2023 and compares cost-effective scenarios to alternative scenarios with institutional, geophysical and technological feasibility constraints and enablers informed by previous literature. Our results show that the most ambitious mitigation trajectories with updated climate information still manage to limit peak warming to below 1.6 °C (‘low overshoot’) with around 50% likelihood. However, feasibility constraints, especially in the institutional dimension, decrease this maximum likelihood considerably to 5–45%. Accelerated energy demand transformation can reduce costs for staying below 2 °C but have only a limited impact on further increasing the likelihood of limiting warming to 1.6 °C. Our study helps to establish a new benchmark of mitigation scenarios that goes beyond the dominant cost-effective scenario design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Prospects for H-mode inhibition in negative triangularity tokamak reactor plasmas

Instability to high toroidal mode number ($\textit{n}$) ballooning modes has been proposed as the primary gradient-limiting mechanism for tokamak equilibria with negative triangularity (NT) (δ) shaping, preventing access to strong H-mode regimes when δ is sufficiently negative. To understand how this mechanism extrapolates to reactor conditions, we model the infinite-$\textit{n}$ ballooning stability as a function of internal profiles and equilibrium shape using a combination of the CHEASE and BALOO codes. While the critical δ required for avoiding 2nd stability to high-$\textit{n}$ modes is observed to depend in a complicated way on various shaping parameters, including the equilibrium inverse aspect ratio, elongation and squareness, equilibria with NT are robustly prohibited from accessing the 2nd stability region, offering the prediction that NT reactors should maintain L-mode-like operation. In order to access high-$\textit{n}$ 2nd stability, the local shear over the entire bad curvature region must be sufficiently negative to overcome curvature destabilization on the low field side. Finally, scalings of the ballooning-limited pedestal height are provided as a function of plasma parameters to aid future scenario design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Combining physics-based and data-driven models for quantitatively accurate plasma profile prediction that extrapolates well; with application to DIII-D, AUG, and ITER tokamaks

For design, scenario planning, and control, ITER and all other envisioned tokamaks rely on a variety of statistical and physics-based models to extrapolate to unseen regimes; most notably from low plasma current to high. A 'meta-learning' methodology for combining the accuracy of data-driven models with the generalizability of physics-based models is described and tested, yielding a 5–10 percent improvement in performance beyond either alone for the task of extrapolating time-dependent plasma profile prediction from low- to high- plasma current DIII-D tokamak discharges. Meanwhile, it is shown that both machine learning models extrapolated far-distribution and state-of-the-art 'physics-based' profile predictors fare worse than merely assuming plasma profiles do not change from their initial values. Finally, a variety of other mechanisms for helping data-driven models generalize—transfer learning, adding contextual information from physics simulators, and adding data from the ASDEX Upgrade tokamak—are attempted for similar extrapolation tasks but, in the methodology used in this paper, yield no significant improvement beyond simple data-driven models. Results are summarized in figures 15 and 16.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States

Climate change impacts on watersheds can potentially exacerbate water scarcity issues where water serves multiple purposes including hydropower. The long-term management of water and energy resources is still mostly approached in a siloed manner at different basins or watersheds, failing to consider the potential impacts that may concurrently affect many regions at once. There is a need for a large-scale hydropower modeling framework that can examine climate impacts across adjoining river basins and balancing authorities (BAs) and provide a periodic assessment at regional to national scales. Expanding from our prior assessment only for the United States (US) federal hydropower plants, we enhance and extend two regional hydropower models to cover over 85% of the total hydropower nameplate capacity and present the first contiguous US-wide assessment of future hydropower production under Coupled Model Intercomparison Project phase 6’s high-end Shared Socioeconomic Pathway 5-8.5 emission scenario using an uncertainty-aware multi-model ensemble approach. We present regional hydropower projections, using both BA regions and US Hydrologic Subregions (HUC4s), to consistently inform the energy and water communities for two future periods—the near-term (2020–2039) and the mid-term (2040–2059) relative to a historical baseline period (1980–2019). We find that the median projected changes in annual hydropower generation are typically positive—approximately 5% in the near-term, and 10% in the mid-term. However, since the risk of regional droughts is also projected to increase, future planning cannot overly rely on the ensemble median, as the potential of severe hydropower reductions could be overlooked. The assessment offers an ensemble of future hydropower generation projections, providing regional utilities and power system operators with consistent data to develop drought scenarios, design long duration storage and evaluate energy infrastructure reliability under intensified inter-annual and seasonal variability.

13 HYDRO ENERGY↗
DOE OSTI2021

Assessing the impact of demand response on peak demand in a developing country: The case of Ghana

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response refers to consumer actions that change the utility load profile in a way that reduces costs or improves grid security by applying price signals and automated load shedding technologies. The methodologies that are used to achieve demand response can hardly be applicable in developing countries. Peak pricing of electricity, for instance, can hardly be implemented in many developing countries as high prices would disproportionately affect the many low-income households who do not have the capacity to take action to avoid paying high peak prices. This study aims to develop demand response methodology that can be applied in developing countries to achieve residential peak demand reduction. We use a consumer preference survey to develop a methodology suitable for developing countries. The method of diversified demand is used with energy audit and monitored data to estimate the potential peak load reduction and its cost-effectiveness for Ghana. Results show that peak reduction of 15-210 MW is expected by 2040 with a positive return on investment of 2-22% for all designed scenarios.

Diawuo, FA↗
DOE OSTI2021

Energy consumption and charging load profiles from long-haul truck electrification in the United States

Abstract The urgent need to decarbonize the transportation sector combined with falling battery prices has spurred industry and policy interest in long-haul truck electrification. The charging behavior and resulting loads from electrified long-haul freight trucks are crucial for the smooth operation of the electric grid and have far-reaching environmental impacts (e.g., greenhouse gas and other air pollutant emissions). However, the aggregate energy impact of a fleetwide shift to electrified long-haul freight trucking has not been explored. This study combines electric truck design scenarios, bottom-up truck weight modeling, vehicle energy modeling, large-scale truck traffic data, and simulation of likely operation and charging behaviors to estimate end-use energy consumption and location-specific hourly charging loads for a national fleet of long-haul electric trucks. Relative to a fleet of future diesel trucks, electrification would reduce direct end-use energy consumption by 0.9 × 10 18 J (0.9 quadrillion BTU), but electrification might increase life cycle energy consumption depending on the electricity source. The electricity required to charge long-haul electric trucks is equivalent to five percent of annual electricity consumption in the United States (US). The simulated truck charging loads peak during the day across the US grid regions, but the charging peaks’ exact timing is sensitive to when trucks are dispatched for operation. The load shapes suggest that electric trucks’ charging loads can coincide with peaks in solar power generation, and planning could enable on- or off-site integration between truck charging stations and renewable electricity generation.

Tong, Fan (ORCID:0000000346613956)↗
DOE OSTI2021

Bayesian analysis of a future β decay experiment's sensitivity to neutrino mass scale and ordering

Bayesian modeling techniques enable sensitivity analyses that incorporate detailed expectations regarding future experiments. A model-based approach also allows one to evaluate inferences and predicted outcomes, by calibrating (or measuring) the consequences incurred when certain results are reported. In this work, we present procedures for calibrating predictions of an experiment's sensitivity to both continuous and discrete parameters. Using these procedures and a new Bayesian model of the β-decay spectrum, we assess a high-precision β-decay experiment's sensitivity to the neutrino mass scale and ordering for one assumed design scenario. We find that such an experiment could measure the electron-weighted neutrino mass within ~40 meV after 1 year (90% credibility). Neutrino masses > 500 meV could be measured within ≈5 meV. Using only β decay and external reactor neutrino data, we find that next-generation β-decay experiments could potentially constrain the mass ordering using a two-neutrino spectral model analysis. By calibrating mass ordering results, we identify reporting criteria that can be tuned to suppress false ordering claims. In some cases, a two-neutrino analysis can reveal that the mass ordering is inverted, an unobtainable result for the traditional one-neutrino analysis approach.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Exploring Demographic Factors Behind the User Preferences in Ridesharing Services

Ridesharing is an increasingly prevalent form of transportation. Personal and pooled rideshare services are the two modes of ridesharing available on the market. While personal rideshare features higher time efficiency and better service experience, especially in terms of privacy, pooled rideshare has better energy efficiency and can reduce traffic congestion. To encourage users to utilize pooled rideshare, it is crucial to understand the factors behind preferences between pooled and personal rideshare services. This study conducted a survey study on a sample of 2,884 participants from the U.S. The stated-choice method was employed to collect the usage rate of pooled rideshare in designed scenarios. A detailed analysis of pooled rideshare usage rates among participants from different demographic backgrounds was performed. The results demonstrated demographic factors related to variations in pooled rideshare usage rates. Findings from this study explore the impacts of demographic factors on people's choices in ridesharing and provide important information for the modeling and optimization of ridesharing transportation systems.

Su, Haotian↗
DOE OSTI2026

An Acid-Free, Temperature-Based Cation Contamination Removal Strategy for PEM Water Electrolysis

It is widely understood that the durability and reliability of polymer electrolyte membrane (PEM) water electrolyzers are heavily dependent on feedwater purity, with cation contaminants that originate from incomplete water purification and balance of plant materials significantly harming electrolyzer performance. However, contamination remains a challenge and a common cause of failure at the stack level, indicating the need for strategies to recover the performance of contaminated cells. In this study, we investigate the effects of temperature on the uptake, electrochemical impacts, and removal of contaminant calcium and iron cations. Lower operating temperatures increase the sensitivity of the cell performance to contaminant cations, while also decreasing cation uptake and promoting contaminant removal. Computational charge transfer modelling shows that lower temperature increases the concentration of contaminant at the cathode and facilitates their removal from the cell. By testing single cells under scenarios designed to mimic stack temperature dynamics, we investigate low-temperature operation as an approach to stack-relevant contaminant recovery. Together, these results demonstrate that the low-temperature recovery approach is a promising approach for acid-free contamination recovery for PEM water electrolysis to promote stack reliability and durability.

08 HYDROGEN↗
DOE OSTI2020

Revisiting the Terawatt Challenge

Richard E. Smalley, in 2003, defined the Terawatt (TW) Challenge as “Adapting our energy infrastructure to simultaneously address diminishing oil resources and rising levels of atmospheric CO 2 .” Smalley, best known for the discovery of C 60 , for which he received the 1996 Nobel Prize in Chemistry, continued to address the challenges of anthropomorphic and natural global energy flows until he passed away in 2005. Smalley challenged the world to transform the energy sector. He envisioned electricity transmitted by high-voltage direct current (DC) lines from massively deployed solar plants in sunny areas and remotely sited nuclear plants. He also envisioned using advanced batteries for local storage of energy. To meet the needs of ~10 people in a world with a dwindling oil supply, Smalley asserted that the world would need to transform its fossil-fuel-driven 14-TW (average power) energy used in 2003 to a largely renewable-energy-driven 30–60 TW (average power) in 2050. This would be possible only if solar-electricity costs could be drastically reduced. The challenges associated with this transition have been called the “Terawatt Challenge.” Fifteen years later, solar-module costs have been reduced by tenfold and annual deployment of solar photovoltaic (PV) modules has grown by a factor of 100,from ~1 gigawatt (GW) in 2004 to ~100 GW in 2018, with a total of 500 GW installed worldwide, producing 2% of the planet’s electricity. As global installed solar generating capacity approaches1 TW, we revisit Smalley’s TW challenge to identify what has changed and quantify the TW Challenge for a baseline scenario and for two scenarios designed as upper and lower bounds determined by the degree we implement electrification and storage. In this paper, we show that the energy choices we make today will dramatically affect the magnitude of future global energy requirements.

SOLAR ENERGY↗
DOE OSTI2025

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗
NASA NTRS1981

Issues related to line-oriented flight training

The use of a training simulator along with carefully structured, detailed, line trip scenarios was envisioned by NASA as a means of providing a controllable, repeatable way to observe line crews in a highly realistic simulation of their working environment and obtain better understanding operationally significant human factors problems and issues. Relevant research done by the agency and the results of full-mission simulation scenarios revealed potential implications for flight training. Aspects to be considered in creating training programs closely related to the actual line environment with a total crew application in real world incident experiences include: (1) operational, environmental, equipment, and crew problems in scenario design; (2) real time line oriented flight training operation; (3) performance assessment and debriefing; (4) instructor qualification and training; and (5) other issues such as ub un initial, transition, and upgrade training; procedures developent and evaluation, and equipment evaluation.

Lauber, J. K.↗
NASA NTRS1985

Earth to space dc to dc power transmission system utilizing a microwave beam as source of energy for electric propelled interorbital vehicles

The paper contributes to the credibility of an electric propelled interorbital transportation system by introducing a new low-mass source of continuous dc power for electric propulsion and illustrating how the source can be economically tied to an electric utility on earth by an electronically steered microwave beam. The new thin-film rectenna, which functions as the receiving end of an earth-to-space microwave power transmission system is described. It is easily fabricated, is over 80 percent efficient, has a specific mass of no more than 2 kilograms per kilowatt of continuous dc power output, and is well adapted for deployment in space. The paper then describes a complete system consisting of the interorbital vehicle and the microwave power transmission system that supplies it with power. A design scenario is used to obtain performance data from the system in terms of vehicle transfer times, payload fractions, and costs. Electric energy costs are found to be less than $1000 per kilogram of payload delivered to geosynchronous orbit from low-earth orbit.

Brown, W. C.↗
NASA NTRS1988

On-orbit technology experiment facility definition

A study was conducted to identify on-orbit integrated facility needs to support in-space technology experiments on the Space Station and associated free flyers. In particular, the first task was to examine the proposed technology development missions (TDMX's) from the model mission set and other proposed experimental facilities, both individually and by theme, to determine how and if the experiments might be combined, what equipment might be shared, what equipment might be used as generic equipment for continued experimentation, and what experiments will conflict with the conduct of other experiments or Space Station operations. Then using these results, to determine on-orbit facility needs to optimize the implementation of technology payloads. Finally, to develop one or more scenarios, design concepts, and outfitting requirements for implementation of onboard technology experiments.

Russell, Richard A.↗