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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Continuation of advanced crew procedures development techniques

An operational computer program, the Procedures and Performance Program (PPP) which operates in conjunction with the Phase I Shuttle Procedures Simulator to provide a procedures recording and crew/vehicle performance monitoring capability was developed. A technical synopsis of each task resulting in the development of the Procedures and Performance Program is provided. Conclusions and recommendations for action leading to the improvements in production of crew procedures development and crew training support are included. The PPP provides real-time CRT displays and post-run hardcopy output of procedures, difference procedures, performance data, parametric analysis data, and training script/training status data. During post-run, the program is designed to support evaluation through the reconstruction of displays to any point in time. A permanent record of the simulation exercise can be obtained via hardcopy output of the display data and via transfer to the Generalized Documentation Processor (GDP). Reference procedures data may be transferred from the GDP to the PPP. Interface is provided with the all digital trajectory program, the Space Vehicle Dynamics Simulator (SVDS) to support initial procedures timeline development.

Arbet, J. D.↗
NASA NTRS1986

Balloon gondola diagnostics package

In order to define a new gondola structural specification and to quantify the balloon termination environment, NASA developed a balloon gondola diagnostics package (GDP). This addition to the balloon flight train is comprised of a large array of electronic sensors employed to define the forces and accelerations imposed on a gondola during the termination event. These sensors include the following: a load cell, a three-axis accelerometer, two three-axis rate gyros, two magnetometers, and a two axis inclinometer. A transceiver couple allows the data to be telemetered across any in-line rotator to the gondola-mounted memory system. The GDP is commanded 'ON' just prior to parachute deployment in order to record the entire event.

Cantor, K. M.↗
NASA NTRS1999

Aviation System Analysis Capability Air Carrier Investment Model-Cargo

The purpose of the Aviation System Analysis Capability (ASAC) Air Cargo Investment Model-Cargo (ACIMC), is to examine the economic effects of technology investment on the air cargo market, particularly the market for new cargo aircraft. To do so, we have built an econometrically based model designed to operate like the ACIM. Two main drivers account for virtually all of the demand: the growth rate of the Gross Domestic Product (GDP) and changes in the fare yield (which is a proxy of the price charged or fare). These differences arise from a combination of the nature of air cargo demand and the peculiarities of the air cargo market. The net effect of these two factors are that sales of new cargo aircraft are much less sensitive to either increases in GDP or changes in the costs of labor, capital, fuel, materials, and energy associated with the production of new cargo aircraft than the sales of new passenger aircraft. This in conjunction with the relatively small size of the cargo aircraft market means technology improvements to the cargo aircraft will do relatively very little to spur increased sales of new cargo aircraft.

Johnson, Jesse↗
NASA NTRS2016

Analyzing Double Delays at Newark Liberty International Airport

When weather or congestion impacts the National Airspace System, multiple different Traffic Management Initiatives can be implemented, sometimes with unintended consequences. One particular inefficiency that is commonly identified is in the interaction between Ground Delay Programs (GDPs) and time based metering of internal departures, or TMA scheduling. Internal departures under TMA scheduling can take large GDP delays, followed by large TMA scheduling delays, because they cannot be easily fitted into the overhead stream. In this paper we examine the causes of these double delays through an analysis of arrival operations at Newark Liberty International Airport (EWR) from June to August 2010. Depending on how the double delay is defined between 0.3 percent and 0.8 percent of arrivals at EWR experienced double delays in this period. However, this represents between 21 percent and 62 percent of all internal departures in GDP and TMA scheduling. A deep dive into the data reveals that two causes of high internal departure scheduling delays are upstream flights making up time between their estimated departure clearance times (EDCTs) and entry into time based metering, which undermines the sequencing and spacing underlying the flight EDCTs, and high demand on TMA, when TMA airborne metering delays are high. Data mining methods (currently) including logistic regression, support vector machines and K-nearest neighbors are used to predict the occurrence of double delays and high internal departure scheduling delays with accuracies up to 0.68. So far, key indicators of double delay and high internal departure scheduling delay are TMA virtual runway queue size, and the degree to which estimated runway demand based on TMA estimated times of arrival has changed relative to the estimated runway demand based on EDCTs. However, more analysis is needed to confirm this.

traffic management advisor↗
NASA NTRS2020

Benefit Assessment of the Integrated Demand Management Concept for Multiple New York Metroplex Airports

Benefits of the Integrated Demand Management (IDM) concept were assessed utilizing a newly developed automated simulation capability called ‘Traffic Management Initiative Automated Simulation (TMIAutoSim).’ The IDM concept focuses on improving traffic flow management (TFM) by coordinating the FAA’s strategic Traffic Flow Management System (TFMS) with its more tactical Time-Based Flow Management (TBFM) system. The IDM concept leverages a new TFMS capability called Collaborative Trajectory Options Program (CTOP) to strategically pre-condition traffic demand flowing into a TBFM-managed arrival environment, where TBFM is responsible for tactically managing traffic by generating precise arrival schedules. The IDM concept was developed over a multi-year effort, focusing on solving New York metroplex airport arrival problems. TMIAutoSim closely mimics NASA’s high-fidelity simulation capabilities while enabling more data to be collected at higher speed. Using this new capability, the IDM concept was evaluated using realistic traffic across various weather scenarios. Six representative weather days were selected after clustering three months of historical data. For those selected six days, Newark Liberty International Airport (EWR) and LaGuardia Airport (LGA) arrival traffic scenarios were developed. For each selected day, the historical data were analyzed to accurately simulate actual operations and the weather impact of the day. The current day operations and the IDM concept operations were simulated for the same weather scenarios and the results were compared. The selected six days were categorized into two groups: ‘clear weather’ for days without Ground Delay Programs (GDP) and ‘convective weather’ for days with GDP and significant weather around New York metroplex airports. For the clear weather scenarios, IDM operations reduced last minute, unanticipated departure delays for short-haul flights within TBFM control boundaries with minimal to no impact on throughput and total delay. For the convective weather scenarios, IDM significantly reduced delays and increased throughput to the destination airports.

Traffic Management Initiative Automated Simulation↗
DOE OSTI2020

Considerations for Long-Term Load Forecasting in Morocco

There are many factors that determine how demand for electricity may change over time. These factors include GDP, population size, and technology diffusion and adoption. We employ a simple extrapolation of current trends in Morocco GDP to estimate how the peak demand and annual consumption may change through the year 2030. We discuss the many factors that this approach does not take into account (such as adoption of air conditioning, electric vehicles, and distributed generation).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling receptor flexibility in the structure-based design of KRAS G12C inhibitors

KRAS has long been referred to as an ‘undruggable’ target due to its high affinity for its cognate ligands (GDP and GTP) and its lack of readily exploited allosteric binding pockets. Recent progress in the development of covalent inhibitors of KRAS G12C has revealed that occupancy of an allosteric binding site located between the α3-helix and switch-II loop of KRAS G12C —sometimes referred to as the ‘switch-II pocket’—holds great potential in the design of direct inhibitors of KRAS G12C . In studying diverse switch-II pocket binders during the development of sotorasib (AMG 510), the first FDA-approved inhibitor of KRAS G12C , we found the dramatic conformational flexibility of the switch-II pocket posing significant challenges toward the structure-based design of inhibitors. Here, we present our computational approaches for dealing with receptor flexibility in the prediction of ligand binding pose and binding affinity. For binding pose prediction, we modified the covalent docking program CovDock to allow for protein conformational mobility. This new docking approach, termed as FlexCovDock, improves success rates from 55 to 89% for binding pose prediction on a dataset of 10 cross-docking cases and has been prospectively validated across diverse ligand chemotypes. For binding affinity prediction, we found standard free energy perturbation (FEP) methods could not adequately handle the significant conformational change of the switch-II loop. We developed a new computational strategy to accelerate conformational transitions through the use of targeted protein mutations. Using this methodology, the mean unsigned error (MUE) of binding affinity prediction were reduced from 1.44 to 0.89 kcal/mol on a set of 14 compounds. These approaches were of significant use in facilitating the structure-based design of KRAS G12C inhibitors and are anticipated to be of further use in the design of covalent (and noncovalent) inhibitors of other conformationally labile protein targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Potential reductions in fine particulate matter and premature mortality following implementation of air pollution controls on coal-fired power plants in India

Coal-fired power plants (CFPPs) account for > 70% of electricity generation in India, but < 5% of facilities have installed technologies for sulfur dioxide (SO 2 ) and nitrogen oxide (NO X ) removal. Emissions of these pollutants lead to the formation of fine particulate matter (PM 2.5 ) and an increased risk of premature mortality for exposed populations. Here, we use a nested version of the GEOS-Chem global chemical transport model (0.5° × 0.625° resolution) for India to estimate reductions in PM 2.5 concentrations that could have been achieved by implementing existing emission control technologies like flue-gas desulfurization (FGD) and/or selective catalytic reduction (SCR). We quantify the associated burden of disease using the integrated exposure response (IER) and global exposure mortality model (GEMM) functions and compare the costs of premature mortality to those for FGD installation. Model simulations for 2010 suggest installation of FGD would have reduced mean annual PM 2.5 concentrations across India by 8%, compared to 3% with SCR installation, and 11% with both FGD and SCR. A 7–28% reduction in PM 2.5 was simulated for local communities closest to CFPPs (same model grid cell), leading to up to 17% reduction in annual premature mortality. Overall, more than 0.21–0.48 million premature deaths would have been avoided over a 10-year period if FGD had been implemented on all CFPPs, compared to 0.09–0.21 million with SCR and 0.22–0.72 million with both FGD and SCR. Benefits associated with such actions are approximately $\$18.1$–$\$604$ billion USD per year, which is equivalent to ~ 0.44 to 10% of India’s GDP. These results suggest that monetary benefits from avoided premature mortality far outweigh the capital and operational costs of FGD and/or SCR installation of $\$19.5$ billion and/or $\$32.8$ billion per year, respectively. This information is essential because the high costs of installation and operation are often given as reasons for delaying installation and commissioning. Finally, we conclude that policy actions to control air pollution from CFPPs are economically justifiable.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2020

Assessing concurrent effects of climate change on hydropower supply, electricity demand, and greenhouse gas emissions in the Upper Yangtze River Basin of China

Hydropower importantly provides flexible low-carbon electricity, however, climate change will affect the hydropower system through altering hydrologic regimes while also affecting electricity demands for heating and cooling that hydropower resources serve. This study assesses the effect of climate change on hydropower and electricity demand in the Upper Yangtze River Basin (UYRB) in China on the regional net electric load and greenhouse gas (GHG) emissions. This is accomplished by using climate projections from five global climate models (GCMs) to simultaneously force (1) a physically-based hydrological model and a statistically-based hydropower model to estimate the future generating capacity of 21 large hydropower plants in the UYRB and (2) an empirical electricity demand model accounting for socioeconomic and climatic factors. Under climate change, the projected hydropower generation in the UYRB tends to increase in the 21st century but is far less than the increase in electricity demand, increasing the gap between demand and supply. Future increases in overall electricity demand are driven by GDP growth, but climate change will alter the distribution of the seasonal electricity demand. Climate warming decreases electricity demand for heating in winter and increases electricity demand for cooling in summer, but ultimately increases demand. Meanwhile, there is an increasing mismatch between electricity demand and hydropower supply associated with inter- and intra-annual variations, owing to the temporal climate change and increase in compound climate extremes (droughts and heatwaves). Finally, meeting the gap between supply and demand due to climate change is estimated to contribute 79.0–184.6 and 50.6–316.2 MMT CO 2e /yr of additional GHG emissions by the mid and end of 21st century, respectively.

13 HYDRO ENERGY↗
DOE OSTI2021

Global Biodiversity Implications of Alternative Electrification Strategies Under the Shared Socioeconomic Pathways

Addressing climate mitigation while meeting global electrification goals will require major transitions from fossil-fuel dependence to large-scale renewable energy deployment. However, renewables require significant land assets per unit energy and could come at high cost to ecosystems, creating potential conflicts between global climate mitigation and biodiversity conservation. Here, we explore the potential biodiversity implications of alternative future global electrification pathways as depicted under the Shared Socioeconomic Scenarios (SSPs), i.e., alternative trends in societal development. We examined the intersection of high-resolution estimates of global energy densities for ten renewable and conventional technologies with global richness data to estimate technology-specific biodiversity footprints (species per GWh), whereas a Cumulative Biodiversity Impact (CBI) score was used to assess land and biodiversity outcomes of alternative scenarios. Downscaled electricity generation scenarios (2020-2100) were also constrained by alternative land conservation and energy development policies. Unexpectedly, variation among SSPs did not exhibit a clear tradeoff between global climate mitigation and CBI. Rather, CBIs were an outcome of total infrastructure development to meet electricity demand (from population growth and GDP) and the total magnitude of renewable energy development and storage technologies. Renewables assembled along a spectrum from land sharing to sparing. At the land sharing end, biomass-powered electricity from dedicated crops contributed the most to biodiversity impacts due to low energy density, whereas land-sparing technologies (solar) caused more-intense land degradation, but in smaller areas. Our results suggest that local land conservation practices and strategies promoting energy diversification could have greater implications for future biodiversity conflicts than global socioeconomic drivers.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Disjunctive optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems

This paper proposes a new optimization model and algorithm for long-term capacity expansion planning of reliable power generation systems. The model optimizes both investment decisions (e.g., size, location, and time to install, retire and decommission facilities) and operation decisions (e.g., on/off status, operating capacity, and expected power output). It is also able to optimize reserve systems (or backup systems), as well as the main systems, to improve power systems reliability. An impact of operational strategies of generators (i.e., participating in electricity production vs. remaining as idle units during operation) on power systems reliability is considered. Probability of equipment failures and capacity failure states are used to rigorously estimate the power systems reliability depending on design and operation strategies. The optimization model is formulated with Generalized Disjunctive Programming (GDP), which is reformulated as a mixed-integer linear programming (MILP) model using the Hull relaxation. Two reliability-related penalties, such as downtime penalty and unmet demand penalty, are included in the objective function to maximize reliability while minimizing the total net present cost. Furthermore, a bilevel decomposition with tailored cuts is developed to reduce computational times of the multi-scale optimization model. The effectiveness of the proposed model is shown by comparing the results with the results obtained from the expansion planning models that do not explicitly consider reliability. In conclusion, we also show that the proposed bilevel decomposition is computationally efficient for solving large scale problems through 5-years and 10-years planning case studies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Linear model decision trees as surrogates in optimization of engineering applications

Machine learning models are promising as surrogates in optimization when replacing difficult to solve equations or black-box type models. This work demonstrates the viability of linear model decision trees as piecewise-linear surrogates in decision-making problems. Linear model decision trees can be represented exactly in mixed-integer linear programming (MILP) and mixed-integer quadratic constrained programming (MIQCP) formulations. Furthermore, they can represent discontinuous functions, bringing advantages over neural networks in some cases. We present several formulations using transformations from Generalized Disjunctive Programming (GDP) formulations and modifications of MILP formulations for gradient boosted decision trees (GBDT). We then compare the computational performance of these different MILP and MIQCP representations in an optimization problem and illustrate their use on engineering applications. Importantly, we observe faster solution times for optimization problems with linear model decision tree surrogates when compared with GBDT surrogates using the Optimization and Machine Learning Toolkit (OMLT).

42 ENGINEERING↗
DOE OSTI2025

Roadmap to reach global net-zero emissions for developing regions by 2085

As climate change intensifies, determining a developing region’s role in achieving net-zero emissions worldwide is crucial. However, regional efforts, considering historical emissions, remain underexplored. Here, we assess energy system changes, technology adoption, and investments needed for developing regions, including five major- and minor-emitting nations. Our analysis, using an integrated assessment model, shows a large gap in regional efforts toward global net-zero emissions, stemming from the necessary shift of energy systems to low-carbon resources. The use of new technologies, like electric vehicles, hydrogen, and carbon capture, varies by region, with the highest adoption required between 2020 and 2030. Financing this shift needs an average gross domestic product (GDP) investment rise of 0.464% in minor-emitting regions and up to 2.1% in major-emitting regions by 2085. Our results could guide policies and support setting quantifiable targets for developing nations. The findings are key to facilitating strategic technology use and finance mobilization to achieve a carbon-neutral future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Revealing the mechanism of action of a first-in-class covalent inhibitor of $\mathrm{KRASG12C}$ $\mathrm{(ON)}$ and other functional properties of oncogenic $\text{KRAS}$ by 31 P $\mathrm{NMR}$

Individual oncogenic KRAS mutants confer distinct differences in biochemical properties and signaling for reasons that are not well understood. KRAS activity is closely coupled to protein dynamics and is regulated through two interconverting conformations: state 1 (inactive, effector binding deficient) and state 2 (active, effector binding enabled). Here, we use 31 P NMR to delineate the differences in state 1 and state 2 populations present in WT and common KRAS oncogenic mutants (G12C, G12D, G12V, G13D, and Q61L) bound to its natural substrate GTP or a commonly used nonhydrolyzable analog GppNHp (guanosine-5'-[(β,γ)-imido] triphosphate). Our results show that GppNHp-bound proteins exhibit significant state 1 population, whereas GTP-bound KRAS is primarily (90% or more) in state 2 conformation. This observation suggests that the predominance of state 1 shown here and in other studies is related to GppNHp and is most likely nonexistent in cells. We characterize the impact of this differential conformational equilibrium of oncogenic KRAS on RAF1 kinase effector RAS-binding domain and intrinsic hydrolysis. Through a KRAS G12C drug discovery, we have identified a novel small-molecule inhibitor, BBO-8956, which is effective against both GDP- and GTP-bound KRAS G12C. We show that binding of this inhibitor significantly perturbs state 1–state 2 equilibrium and induces an inactive state 1 conformation in GTP-bound KRAS G12C. In the presence of BBO-8956, RAF1–RAS-binding domain is unable to induce a signaling competent state 2 conformation within the ternary complex, demonstrating the mechanism of action for this novel and active-conformation inhibitor.

31P NMR↗
DOE OSTI2020

Dynamics of virtual water networks: Role of national socio-economic indicators across the world

Intensified water usage due to rapid industrialization is often dictated by economic policies based on monetary growth rather than sustainable use of environmental resources. In addition, interdependence within economic sectors further interweaves water usage through product transactions, which further makes it difficult to quantify the dynamics of hydro-economic systems at regional, national and global scale. In this study, we investigated the dynamics of domestic virtual water networks (VWN) of 189 countries based on concept of information theory by quantifying network metrics that describes VWN flow capacity, robustness, efficiency and flexibility. These networks represent virtual water interconnected through economic sectors within a specified country built based on environmentally extended multi region input output (EE-MRIO) approach. We further estimated trends associated with network metrics, as well as coupling intensity between metrics with respect to socio-economic indicators, such as, population, Gross Domestic Product (GDP) and Gross National Income (GNI). It was observed that capacity and flexibility of VWNs are strongly and positively correlated indicating that a high capacity VWN can be more flexible. Our results also indicate that, in general a higher percentage of developing countries (i.e. both least developing and developing nations) have exhibited increasing trends in capacity, robustness, efficiency and flexibility of VWN compared to developed nations. It was revealed that the dynamics of VWNs are positively coupled with socio-economic growth for few countries, which indicates the sustainable behavior of VWN with socio-economic growth. Our results argue that the information theory-based metrics by embedding water footprints can holistically capture sustainability aspect of the VWN dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deuterium transport and retention properties of representative fusion blanket structural materials

Reduced activation ferritic-martensitic (RAFM) steels have been developed for decades for use as fusion blanket structural materials, and have advantages in both mechanical properties and irradiation resistance following careful engineering of the microstructure. However, the hydrogen isotope behavior in these proposed fusion structural materials is not well understood, but is important to assess since it impacts the fusion reactor safety and self-sufficient tritium fuel cycle. Here, we investigated deuterium transport and retention in representative advanced RAFM steels, including castable nanostructured alloys (CNAs), and oxide-dispersion-strengthened (ODS) steels. A gas-driven permeation (GDP) system was used to measure the permeability, diffusivity and solubility of the studied materials, covering the temperature range from 623 K to 873 K, and the loading pressures from 1.8 x 10 4 to 1.0 x 10 5 Pa. The results indicated that the deuterium permeability has little material dependence. In contrast, the deuterium diffusivity of the studied materials showed significant variation. The deuterium diffusivity in ODS steels is one order of magnitude lower than that in RAFM steels and CNAs, and correspondingly, have an effective solubility that is 2–10 times larger than RAFM steels and CNAs. In addition, thermal desorption spectroscopy (TDS) measurements were performed to assess the deuterium retention and desorption of these materials following a static thermal deuterium charging at 723 Kfor 1 hour under the deuterium pressure of 1.0 x 10 5 Pa. It was found that ODS steels exhibit the highest deuterium retention and have broader desorption peaks. Microstructural features contributing to deuterium retention and impacting deuterium transport are discussed to rationalize the observed deuterium behavior in the studied RAFM steels.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Policy support and technology development trajectory for renewable natural gas in the U.S.

Renewable natural gas (RNG) is a clean alternative to fossil natural gas, which can be used as transportation fuel, among other applications. This study projects the development trajectory of RNG and evaluates its impacts on the future U.S. transportation market using a hybrid computable general equilibrium model. This analysis considers various factors and uncertainties affecting RNG production, such as technology development, market conditions, competition with other advanced biofuels, and national and state policies. In 2050, RNG production will grow to 2.7 billion gallons (10 billion liters), mostly from swine manure, under current policy provisions. This will lead to a reduction in greenhouse gas (GHG) emissions by 58.56 million metric tonne of CO 2e in 2050. Analysis of different technology cases finds RNG from animal manure to be predominant, while RNG from corn stover and cellulosic ethanol are less competitive. Furthermore, a high mandatory target of 1 billion gallons will drive RNG production higher by 8–18 %, while an extended 2 nd -generation biofuel production tax credit will mostly increase cellulosic ethanol production. The model also finds RNG production being affected by uncertainties in market conditions, such as GDP growth, fossil fuel prices, and oil and gas supply.

Biomethane↗
DOE OSTI2025

How KRAS Mutations Impair Intrinsic GTP Hydrolysis: Experimental and Computational Investigations

Oncogenic KRAS mutations impair GTP hydrolysis and increase the active GTP-bound KRAS population, which leads to growth-factor-independent cell proliferation and survival of cancer cells. Despite notable successes of small-molecule inhibitors in the treatment of KRASG12C cancer, many of these small-molecule inhibitors preferentially bind to inactive (GDP-bound) mutant KRAS, whose availability is limited by the slow rate of intrinsic GTP hydrolysis. A better understanding of how KRAS mutations impair intrinsic hydrolysis is important for designing more effective small-molecule therapeutics. In this work, experimental and computational approaches were utilized to investigate how the most important oncogenic mutations affect the intrinsic hydrolysis of GTP. Here, we found that Q61H, G12V, and G12R mutations impair intrinsic hydrolysis by around 7-fold, 9-fold, and more than 20-fold, respectively, whereas G12A, G12C, G12D, and G13D have less effect. Based on mechanistic investigations, we propose that KRAS mutations impair intrinsic hydrolysis by disrupting the interactions needed to align the nucleophilic water molecule with GTP for nucleophilic attack. These results can assist small-molecule inhibitor design and also benefit the development of other therapeutic strategies, such as rescuing hydrolysis.

Ab Initio↗