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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Integrating equity in transportation scenario planning: A systematic review

To address the growing uncertainties in the future transportation industry, planners and engineers have identified and implemented scenario planning, a multi-step and strategic approach, in long-range transportation planning. A comprehensive examination of how equity is envisioned, planned, and analyzed during this process remains absent, despite several key guidelines of scenario planning exercises. This paper conducts a systematic literature review focusing on how equity has been considered and evaluated in scenario planning. The resources include academic papers, agency reports, and materials from the recent scenario planning conference, the 2nd Conference on Scenario Planning in Transportation hosted by the Transportation Research Board. This paper examines equity in scenario planning in three important ways: 1) the ways equity has been integrated across steps; 2) how equity analysis has evolved; and 3) when it is necessary to consider equity. This work adds value to the existing body of knowledge by presenting the policy implications based on the review of the current scenario planning research and practices. Early policy recommendations include the need for more vertical equity evaluations, the construction of robustness and justice indicators, and the adoption of a flexible mindset of planning for rather than being fixated on a single scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

The National Transmission Planning Study: Chapter 2: Long-Term U.S. Transmission Planning Scenarios

The National Transmission Planning Study (NTP Study) was led by the U.S. Department of Energy's Grid Deployment Office, in partnership with the National Renewable Energy Laboratory and Pacific Northwest National Laboratory. The study sought to develop new national grid-scale planning tools and methods that can be used by industry, especially when planning for interregional transmission capacity needs; identify potential transmission solutions that will provide broad-scale benefits to electric customers under a wide range of potential futures; inform planning processes for regional and interregional transmission; and identify interregional and national strategies to maintain grid reliability as the grid transitions, including to a reliance on low- and zero-carbon energy resources. The NTP Study is presented as a collection of six chapters.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
NASA NTRS2024

Applications of Remote Sensing for Land Use Planning Scenarios with Suitability Analysis

In regions undergoing rapid urbanization, such as West Africa, land use planning (LUP) is vital to accommodate growing population and manage natural resources. Suitability analysis modeling is a widely used tool in LUP to determine the extent to which a land area is suitable for a designated purpose, but there is a gap in the integration of remote sensing time series data into land use decisions. The goal of this study was to incorporate remote sensing time series information with suitability analyses to inform LUP decisions in urban areas. In the study area of Kumasi, Ghana, land cover trends and land surface temperature (LST) from 2000 to 2019 were used to understand climate change trends. Suitability analyses determined the fitness of land areas for predetermined uses. These background processes informed a genetic algorithm to project plausible futures for three land use scenarios. One scenario represented current land use planning practices for addressing population growth, another scenario prioritized minimizing climate change impacts while also accommodating population growth, and the final scenario focused on both of these climate and population goals in addition to high density urban development. Each of these scenarios was successful in achieving population accommodation and respective climate change mitigation goals. The results for these scenarios provide insight into plausible land use distributions in 2050 based on different planning approaches. The genetic algorithm was able to effectively develop results for each scenario through the integration of remotely sensed trends and suitability models, providing a novel approach to land use decision-making.

remote sensing time series↗
NASA NTRS2023

Aviation 2072: Scenario Planning for Wicked Problems

The world is changing rapidly. And with it, so are the potential futures for humanity. Many of these potential futures pose hidden threats, while others offer new opportunities for aviation and the broader aerospace community. To mitigate these risks and capitalize on opportunities, organizations must work to deeply understand these potential future scenarios and uncover any underlying drivers. Organizations will be more equipped and informed when making strategic investment decisions by better understanding these threats, opportunities, and drivers . The future scenarios and their threats and opportunities described in this paper were identified through a series of extensive brainstorming workshops, collectively titled MADNESS (Mapping for Aviation Driven by Needs Emergence and Satiating Society). These workshops engaged NASA civil servants and contractors with diverse backgrounds through a facilitated process of future scenario development and critique. The participants were led through exercises focused on a time horizon spanning from 2022 to 2072 and on problems that aviation might solve and or create during this period. From the broad results, two patterns of critical uncertainty emerged: “availability” (scarcity versus abundance) and “transparency” (openness versus security and privacy). The successful iteration and ideation across the MADNESS workshops also suggests a repeatable mechanism for strategic risk exploration across a variety of NASA and industry stakeholders.

Mapping↗
DOE OSTI2024

Scenario Planning Management Actions to Restore Cold Water Stream Habitat: Comparing Mechanistic and Statistical Modeling Approaches

ABSTRACT Under the United States Clean Water Act, states are required to periodically assess state waters to determine compliance with water quality criteria (including temperature) and then to develop total maximum daily loads (TMDLs) for impaired waters as necessary to bring them into compliance. We compared the performance of mechanistic stream temperature models (HeatSource, QUAL2K, and QUAL2Kw) applied to the mainstem of three TMDL watersheds (Middle Fork John Day, OR; Wind River, WA; South Fork Nooksack, WA) with that of spatial stream network (SSN) models applied to the full watersheds and used these to evaluate the potential effectiveness of restoration strategies. SSN models performed well with slightly lesser accuracy (RMSE = 0.47–0.87) for mainstem predictions than mechanistic models (RMSE = 0.4) but provided additional benefits to inform management, including information on spatial and temporal heterogeneity of restoration effectiveness throughout the watershed. Of the four scenarios considered (restoration of riparian zones to potential natural vegetation, channel narrowing, increasing flow by restricting irrigation withdrawals, and combined applications), riparian zone restoration was consistently the most effective in reducing temperatures at the outlet, mainstem, and throughout the watersheds. Predicted restoration effectiveness for thermal regimes varied significantly both within and among watersheds. A focus on water quality criteria exceedance only at the watershed outlet or along the mainstem reach can obscure knowledge of restoration potential for fish habitat in tributaries and headwaters, potential for creation of thermal refuge areas along the mainstem critical for maintaining migration corridors, and thermal regime heterogeneity across space and time.

Fuller, M. R.↗
DOE OSTI2025

Verifying infectious disease scenario planning for geographically diverse populations

In the face of the COVID-19 pandemic, the literature saw a spike in publications for epidemic models, and a renewed interest in capturing contact networks and geographic movement of populations. There remains a general lack of consensus in the modeling community around best practices for spatiotemporal epi-modeling, specifically as it pertains to the infection rate formulation and the underlying contact or mixing model. We mathematically verify several common modeling assumptions in the literature, to prove when certain choices can provide consistent results across different geographic resolutions, population densities and patterns, and mixing assumptions. The most common infection rate formulation, a computationally low cost per capita infection rate assumption, fails the consistency tests for heterogeneous populations and gravity-weighting assumptions. Future modeling efforts in spatiotemporal disease modeling should be wary of this limitation, particularly when working with more heterogeneous or sparse populations. Our results provide guidance for testing that a model preserves desirable properties even when model inputs mask potential problems due to symmetry or homogeneity. We also provide a recipe for performing this type of verification, strengthening decision support tools.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1988

Suggested GOES I-M satellite operational scenarios

Plans for the GOES I-M satellite system are reviewed, focusing on the use of GOES data in severe local storm and tropical cyclone analysis and forecasting. The instrumentation and capabilities of the GOES I-M system, which is expected to be launched beginning in the spring of 1990, are discussed. Sounder and imaging coverage scenarios and scenario timetables are presented.

Shenk, William E.↗
NASA NTRS1986

NASA space plans and scenarios to 2000 and beyond

NASA's research and development plans, as reflected in its missions, goals, and objectives to the year 2000 and beyond, are presented. New starts for the next decade and space program activities are highlighted, including space science and applications, space flight, space stations, space tracking and data systems, and space research and technology. Space programs for the 21st century are also covered.

Source record↗
DOE OSTI2023

Fast model-based scenario optimization in NSTX-U enabled by analytic gradient computation

Model-based optimization offers a systematic approach to advanced scenario planning. In this case, the feedforward-control inputs (actuator trajectories) that are needed to attain and sustain a desired scenario are obtained by solving a nonlinear constrained optimization problem. This class of problems generally minimize a cost function that measures the difference between desired and actual plasma states. Several numerical optimization algorithms, such as sequential quadratic programming, require repeated calculation of the cost function gradients with respect to the input trajectories. Calculating these gradients numerically can be computationally intensive, increasing the time needed to solve the feedforward-control optimization problem. Here, this work introduces a method to analytically calculate these cost function gradients from the current profile evolution model. This can significantly reduce the computational time and allow for fast feedforward-control optimization, which would eventually enable optimal scenario planning between discharges. The performance of the feedforward optimizer with analytical gradients is compared to a traditional optimization algorithm based on numerical gradients for different NSTX-U scenarios. The plasma dynamics in the optimization algorithm are simulated using the Control Oriented Transport SIMulator (COTSIM). Results of the work show that analytical gradients consistently reduce the computation time while achieving trajectories that are comparable to those obtained by traditional optimization algorithms based on numerical gradients.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1986

The impact of physical and mental tasks on pilot mental workoad

Seven instrument-rated pilots with a wide range of backgrounds and experience levels flew four different scenarios on a fixed-base simulator. The Baseline scenario was the simplest of the four and had few mental and physical tasks. An activity scenario had many physical but few mental tasks. The Planning scenario had few physical and many mental taks. A Combined scenario had high mental and physical task loads. The magnitude of each pilot's altitude and airspeed deviations was measured, subjective workload ratings were recorded, and the degree of pilot compliance with assigned memory/planning tasks was noted. Mental and physical performance was a strong function of the manual activity level, but not influenced by the mental task load. High manual task loads resulted in a large percentage of mental errors even under low mental task loads. Although all the pilots gave similar subjective ratings when the manual task load was high, subjective ratings showed greater individual differences with high mental task loads. Altitude or airspeed deviations and subjective ratings were most correlated when the total task load was very high. Although airspeed deviations, altitude deviations, and subjective workload ratings were similar for both low experience and high experience pilots, at very high total task loads, mental performance was much lower for the low experience pilots.

Berg, S. L.↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

cost modeling estimation↗
NASA NTRS2015

Exploring NASA Human Spaceflight and Pioneering Scenarios

The life cycle cost analysis of space exploration scenarios is explored via a merger of (1) scenario planning, separating context and (2) modeling and analysis of specific content. Numerous scenarios are presented, leading to cross-cutting recommendations addressing life cycle costs, productivity, and approaches applicable to any scenarios. Approaches address technical and non-technical factors.

space systems life cycle costs↗
NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗
DOE OSTI2024

Tokamak divertor plasma emulation with machine learning

Abstract Future tokamak devices that aim to create conditions relevant to power plant operations must consider strategies for mitigating damage to plasma facing components in the divertor. One of the goals of MAST-U tokamak operations is to inform these considerations by researching advanced divertor configurations that aid stable plasma detachment. Machine design, scenario planning and detachment control would all greatly benefit from tools that enable rapid calculation of scenario-relevant quantities given some input parameters. This paper presents a method for generating large, simulated scrape-off layer data sets, which was applied to generate a data set of steady-state Hermes-3 simulations of the MAST-U tokamak. A machine learning model was constructed using a Bayesian approach to hyperparameter optimisation to predict diagnosable output quantities given control-relevant input features. The resulting best-performing model, which is based on a feedforward neural network, achieves high accuracy when predicting electron temperature at the divertor target and carbon impurity radiation front position and runs in around 1 ms in inference mode. Techniques for interpreting the predictions made by the model were applied, and a high-resolution parameter scan of upstream conditions was performed to demonstrate the utility of rapidly generating accurate predictions using the emulator. This work represents a step forward in the design of machine learning-driven emulators of tokamak exhaust simulation codes in operational modes relevant to divertor detachment control and plasma scenario design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Fish Friendly Water Rules' Impact On the Power Grid with High VRE Levels

Columbia River basin multipurpose reservoirs are operated for hydropower production and many other purposes considering the aquatic habitat of the river basin. Specifically, the river basin fish population is a vital element for the tribal community of the river basin. When conventional thermal power plants are retired, hydropower flexibility balances the wind and solar variability of the power grid and provides grid services to maximize the high renewable power absorption. On the other hand, over-reliance on hydropower could harm the river basin fish habitat. For example, water release pulses during peak electricity demand hours and shorter-term water release variation could harm the fish population. Power grid planners, environmentalists, Columbia Basin tribes, hydro regulators, and water resource planners work together to understand the impacts of Columbia River basin operation in a fish-friendly way in the current power grid and power grid with higher renewable power share. We examine different levels of renewable share in the Western Interconnection to understand the multiple weather years and future climate projection and operating scenario impact on the power grid and water system. We measure power grid impacts for various water resources planning scenarios in terms of total system operating cost, system reliability indicators, changes in wind and solar generation and curtailments, local marginal prices, and revenue for hydropower producers. The study results inform reservoir operating rules decisions from hydropower power producers, system operators, other water users, tribes, environmentalists, and other stakeholders.

environmental↗
DOE OSTI2024

Surveillance Workload Divinator (SWORD)

The LANL Surveillance Workload Divinator (SWORD) is a high-level decision support tool that reproduces and predicts the annual values for stockpile and production disassembly and inspections (D&I) and rebuilds. SWORD, a spreadsheet-based tool, can be used to assess the surveillance workload under various planning scenarios. Results are shown graphically and updated dynamically for each weapon system or for the entire stockpile. Surveillance workload is calculated from stockpile surveillance guidance1 and from Production and Planning Directive (P&PD) data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

A User-Facing Metric to Quantify the Quality of Mobility (CRADA Final Report)

The leading urban mobility data analytics firm StreetLight Data, Inc. partnered with the National Renewable Energy Laboratory to explore a commercial version of the Mobility Energy Productivity (MEP) metric. The commercialization effort was aimed to expand the adoption of the metric to key stakeholders in the urban planning space. Research comprised industry analysis, stakeholder feedback and conducting transportation practitioner focus groups. StreetLight concluded that commercialization of MEP is not feasible in the current market because users need a dynamic MEP tool that enables scenario planning. It should be able to calculate a MEP score dynamically (near instantaneous) when different inputs are changed.

33 ADVANCED PROPULSION SYSTEMS↗