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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Performance measurement: A tool for program control

Performance measurement is a management tool for planning, monitoring, and controlling as aspects of program and project management--cost, schedule, and technical requirements. It is a means (concept and approach) to a desired end (effective program planning and control). To reach the desired end, however, performance measurement must be applied and used appropriately, with full knowledge and recognition of its power and of its limitations--what it can and cannot do for the project manager. What is the potential of this management tool? What does performance measurement do that a traditional plan vs. actual technique cannot do? Performance measurement provides an improvement over the customary comparison of how much money was spent (actual cost) vs. how much was planned to be spent based on a schedule of activities (work planned). This commonly used plan vs. actual comparison does not allow one to know from the numerical data if the actual cost incurred was for work intended to be done.

Abell, Nancy↗
NASA NTRS1990

The COLD-SAT experiment for cryogenic fluid management technology

The COLD-SAT spacecraft design experiments are described. COLD-SAT will be placed into an initial 1300 km circular orbit by an Atlas commercial launch vehicle. Electric power, experiment control and data management, attitude control, and propulsive accelarations for the experiments will be provided by the three-axis-controlled spacecraft bus. To provide data on the effects that low gravity levels might have on the heat and mass transfer processes involved, low levels of accelaration will be created. The COLD-SAT experiment will be configured into a module. The spacecraft experiment module will include three liquid hydrogen tanks; fluid transfer, pressurization and venting equipment; and instrumentation. Since the largest tank has helium-purged MLI to prevent ingress and freezing of air on the launchpad, it will contain all the liquid hydrogen at the point of launching. The hydrogen tanking system used for the Centaur upper stage of the Atlas will load and top off this tank. Atlas, with its liquid hydrogen upper stage, large payload fairing, and large launch margin, simplifies COLD-SAT design and integration.

Schuster, J. R.↗
DOE OSTI2022

Lessons Learned on the Interface Between Quantum and Conventional Networking

The future Quantum Internet is expected to be based on a hybrid architecture with core quantum transport capabilities complemented by conventional networking. Practical and foundational considerations indicate the need for conventional control and data planes that (i) utilize extensive existing telecommunications fiber infrastructure, and (ii) provide parallel conventional data channels needed for quantum networking protocols. We propose a quantum-conventional network (QCN) harness to implement a new architecture to meet these requirements. The QCN control plane carries the control and management traffic, whereas its data plane handles the conventional and quantum data communications. We established a local area QCN connecting three quantum laboratories over dedicated fiber and conventional network connections. We describe considerations and tradeoffs for layering QCN functionalities, informed by our recent quantum entanglement distribution experiments conducted over this network.

Alshowkan, Muneer↗
DOE OSTI2024

Macroscopic Traffic Modeling Using Probe Vehicle Data: A Machine Learning Approach

Abstract The macroscopic fundamental diagram (MFD) captures an orderly relationship among traffic flow, density, and speed at the network level. It is a simple yet powerful tool for modeling traffic dynamics in large urban networks with broad application in traffic control and management. However, empirically derived MFDs in urban regions require high-resolution traffic data from the network. Having the network flow and vehicular density estimated at the (granular) census tract level using vehicle probe data, we apply machine learning methods to predict the MFDs across U.S. urban areas and capture the impacts of location-specific input features on the network flow–density relationships at a large scale. The results show that, among the four tested machine learning approaches (Random Forest, XGBoost, Support Vector Machine, and Neural Network), XGBoost delivers the best performance in predicting network traffic flow based on vehicular density and location attributes. Using interaction Shapley Additive explanation (SHAP) values and partial correlation analysis, we examine the factors influencing MFD shapes across different locations. Our empirical findings reveal that across U.S. urban areas, network topology, transportation infrastructure, and land use are primary factors shaping MFD curves, while demand and trip-related factors play a lesser role. Specifically, higher ranking roads, centrality, and development levels correlate positively with network capacity and critical density, whereas negative associations are observed for network connectivity, mixed-use development, and road roughness levels.

Jin, Ling↗
DOE OSTI2022

Development and assessment of prognosis digital twin in a NAMAC system

The nearly autonomous management and control (NAMAC) system is a comprehensive control system to assist plant operations by furnishing control recommendations to operators. Prognosis digital twin (DT-P) is a critical component in NAMAC for predicting action effects and supporting NAMAC decision-making during normal and accident scenarios. To quantifying and reducing uncertainty of machine-learning-based DT-Ps in multi-step predictions, this work investigates and derives insights from the application of three techniques for optimizing the performance of DT-P by long short-term memory recurrent neural networks, including manual search, sequential model-based optimization, and physics-guided machine learning. Finally, sequential model-based optimization and physics-guide machine learning result in smallest errors when the predicting transients are similar to the training data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Blockchain Smart Contract Reference Framework and Program Logic Architecture for Transactive Energy Systems

This paper proposes a reference framework for a transactive energy market based on blockchain. The framework was designed based on the engineering requirements of a distribution-scale market; including participant needs, expected market transactions, and the cybersecurity constructs required to support a fair, secure and efficient market operation. It leverages the existing blockchain primitives to provide clear value propositions to the transactive market, including identity management (access control), data security (integrity), resiliency (decentralization, scalability and performance). The validity of the proposed framework is demonstrated using a real-time 5-min double-auction market. The results highlight its benefits while providing strong validation of applicability to blockchain within transactive energy systems.

Gourisetti, Sri Nikhil Gupta↗
DOE OSTI2024

Hybrid metal additive/subtractive machine tools and applications

Additive manufacturing creates parts by depositing a preform, typically layer by layer. Subtractive manufacturing involves removing material from a preform to create parts. Hybrid machine tools combine both additive and subtractive processes in the same workspace. They can be used to create parts that meet functional tolerance and surface finish requirements, or to create features that are difficult to produce using additive or subtractive processes alone. Here, this paper describes hybrid metal additive/subtractive machine tools. It covers design considerations, sensors and controls, process management, programming and software, and the impact on the design space. It also identifies future research challenges.

42 ENGINEERING↗
DOE OSTI2025

Energy-efficient multimodal mobility networks in transportation digital twins: Strategies and optimization

The study proposes a comprehensive Transportation Mobility (TransitMo) framework covering conceptual design, model formulation, optimization, simulation, and impact analysis of the transportation mobility system. TransitMo is composed of a transportation digital twin developed in Simulation of Urban MObility (SUMO) and an Intelligent Traffic Management and Control Center (ITMCC) that identifies the best ways to improve the movement of people within urban areas using various modes of transportation. This study encompasses advanced modeling techniques, algorithms, and strategic testing to optimize energy efficiency and mobility in a multimodal shared mobility network. TransitMo’s practical applications are exemplified through a city-scaled simulation network in Chattanooga, TN, employing demographic data to analyze historical traffic patterns and forecast future demands. Central to this methodology are three models: the User Preference Model (UP), the Energy Consumption Model (EC), and the System Optimization Model (SO). These models work in concert to iteratively devise the optimal travel incentives and minimize the total system cost in a real-time manner. In conclusion, test results verified that the proposed adaptive incentive program and optimized bus scheduling can improve network performance by increasing public transit ridership.

42 ENGINEERING↗
DOE OSTI2025

Manganese in drinking-water reservoirs: a multi-disciplinary review of current issues, biogeochemical controls, and oxygenation-based management

Decreased water quality and increased treatment costs due to excess manganese (Mn) in drinking-water supplies are critical issues globally. To combat on-going and emerging taste and odour issues with Mn and other contaminants (e.g., algal toxins), many utilities are using engineered oxygenation or aeration (EOA) systems to improve water quality in lakes and reservoirs. Resultant shifts in key biogeochemical and physical processes are still poorly understood, often leading to inefficiently managed systems. Paired with knowledge gaps regarding environmental drivers of Mn and the complexity of Mn redox kinetics, Mn problems persist. This review presents the state of current research in areas critical to optimisation of EOA mitigation of Mn, with focus on i) Mn biogeochemical cycling within drinking-water reservoirs; ii) influences of local catchment geology, hydrology, and land use on Mn dynamics; and iii) Mn management using different EOA approaches. The importance of considering the combined implications of these factors for successful Mn management in reservoirs is highlighted by an evaluation of relevant field-based studies; a wide range in EOA performance is observed, from a 97 % decrease in soluble Mn up to a ∼400 % increase in total Mn. Despite the breadth of studies that consider Mn in water-supply systems, there are still several areas of research which warrant further investigation, including: the influence of natural sources and anthropogenic activities on Mn within a given catchment, Mn speciation and transport in stratified and destratified lakes and reservoirs, and optimal site-specific EOA strategies for Mn mitigation.

Aeration↗
DOE OSTI2021

Robust passivation of CdSeTe based solar cells using reactively sputtered magnesium zinc oxide

Magnesium zinc oxide (MZO, Mg x Zn 1-x O) is a leading emitter for CdTe-based solar cells due to its transparency and the ability to tune its conduction band offset with the absorber. Devices employing alloyed cadmium selenide telluride (CST, CdSe y Te 1-y ) absorbers achieved high efficiency (>19%) using MZO deposited by reactive sputtering over a broad composition range (3.68–3.92 eV, x: 0.20–0.35). Minimal differences in implied and measured open circuit voltage indicate that the contacts are well passivated and highly selective across the spectrum of MZO employed. Device performance insensitivity to MZO composition, which is not observed in CdTe devices, is attributed to the formation of an oxygenated interface layer. Se volatility creates a group VI deficiency at the interface that drives O migration from the MZO into the absorber. This introduces conductivity in the emitter not present in its as-deposited state, contributing to the exceptional performance observed. It is shown that the quality of device passivation depends on the oxidation state of the as-deposited MZO such that intelligent control and management of the reactive sputtering process is required.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Molecular Insights into Geochemical Reactions of Iron-Bearing Minerals: Implications for Hydrogen Geo-Storage

Here, this study investigates the reaction of hydrogen (H 2 ) with pyrite (FeS 2 ), focusing on how temperature and the presence of water influence the reaction pathways and kinetics. Utilizing computational molecular simulations and kinetic analyses, we explore the impact of these factors on the formation of hydrogen sulfide (H 2 S) and related species. First, grand canonical Monte Carlo/molecular dynamics (GCMC/MD) simulations reveal that physical H 2 adsorption occurs in distinct layers on the pyrite surface. In addition, increased temperatures reduce the absolute adsorption capacities. Reactive MD simulations demonstrate that H 2 interacts differently with pyrite under varying conditions. At 298 K, H 2 reacts with pyrite to form HS – , leading to the formation of HS – through covalent bonding with sulfur of pyrite. However, no H 2 S is produced at this temperature, suggesting that a kinetic barrier (i.e., activation energy) may prevent this reaction. At higher temperatures, H 2 S production significantly increases. The presence of water introduces additional complexity to the reaction mechanism. Unlike dry conditions, water enhances H 2 S generation, even at low temperatures. Water also facilitates the formation of additional products, such as SOH, indicating a more intricate chemical environment on the pyrite surface. Our findings identify the association of HS – ions to form H 2 S as the rate-limiting step, with temperature influencing this process. This finding suggests that while the presence of water can create a more dynamic reaction environment, the overall mechanisms leading to H 2 S formation remain consistent. These outcomes suggest the need for developing targeted strategies to manage and control H 2 S emissions within the context of underground hydrogen storage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Performance of Fire Danger Indices and Their Utility in Predicting Future Wildfire Danger Over the Conterminous United States

Abstract Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Asymmetric electrode ionomer for low relative humidity operation of anion exchange membrane fuel cells

The operation of fuel cells under low relative humidity (RH) conditions gives substantial cost and performance benefits. Nonetheless, it is not currently feasible to operate anion exchange membrane fuel cells (AEMFCs) at low RH conditions because current materials for membrane electrode assembly cannot provide sufficient water for the oxygen reduction reaction. In this work, we synthesized polyfluorene ionomers with different ammonium concentrations for anode and cathode to control water management. We designed several asymmetric electrodes that enable high performance under low RH conditions via not only conventional backward water diffusion (anode to cathode) but also forward diffusion (cathode to anode). The AEMFCs using optimized asymmetric electrodes exhibited high H 2 /CO 2 -free air performance (rated power density of circa 540 mW cm -2 at 90 °C under 75% (anode) and 50% RH (cathode) conditions), which is comparable to those of state-of-the-art AEMFCs under nearly water-saturated conditions. The durability of the AEMFCs is excellent, generating 0.6 A cm -2 for >900 h at 80 °C under 50% RH (cathode) conditions. This study demonstrates that high-performance and durable AEMFCs under low RH and high current generating conditions are possible.

25 ENERGY STORAGE↗
DOE OSTI2020

An Unsteady Actuator Line Solver to Enable Adjoint Sensitivity Studies for Wake Steering

This study demonstrates the sensitivity of wind turbine wake steering performance to blade design. An actuator line model was implemented within an unsteady adjoint solver that enables efficient execution of gradient-based optimization and sensitivity studies. After first confirming the feasibility of wake steering by controlling actuator line chord profiles and formulating a suitable objective function for wake position, a sensitivity study was conducted to determine the relative importance of chord length as a function of spanwise position on the resulting turbine wake deflection. The results presented here support the idea that blade design choices play a role in wake control. In a larger context, this study demonstrates a computational framework in which turbine and blade designs can be studied at the individual and farm-wide level to enhance wind plant controllability and manage power output.

17 WIND ENERGY↗
DOE OSTI2022

A Unified Protocol for CRISPR/Cas9-Mediated Gene Knockout in Tephritid Fruit Flies Led to the Recreation of White Eye and White Puparium Phenotypes in the Melon Fly

Abstract Tephritid fruit flies are among the most invasive and destructive agricultural pests worldwide. Over recent years, many studies have implemented the CRISPR/Cas9 genome-editing technology to dissect gene functions in tephritids and create new strains to facilitate their genetics, management, and control. This growing literature allows us to compare diverse strategies for delivering CRISPR/Cas9 components into tephritid embryos, optimize procedures, and advance the technology to systems outside the most thoroughly studied species within the family. Here, we revisit five years of CRISPR research in Tephritidae and propose a unified protocol for candidate gene knockout in fruit flies using CRISPR/Cas9. We demonstrated the efficiency of our protocol by disrupting the eye pigmentation gene white eye (we) in the melon fly, Zeugodacus cucurbitae (Coquillett) (Diptera: Tephritidae). High rates of somatic and germline mutagenesis were induced by microinjecting pre-assembled Cas9-sgRNA complexes through the chorion of embryos at early embryogenesis, leading to the rapid development of new mutant lines. We achieved comparable results when targeting the we orthologue in the oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), illustrating the reliability of our methods when transferred to other related species. Finally, we functionally validated the recently discovered white pupae (wp) loci in the melon fly, successfully recreating the white puparium phenotype used in suppression programs of this and other major economically important tephritids. This is the first demonstration of CRISPR-based genome-editing in the genus Zeugodacus, and we anticipate that the procedures described here will contribute to advancing genome-editing in other non-model tephritid fruit flies.

Entomology↗
DOE OSTI2023

Efficient Network Partitioning: Application for Decentralized State Estimation in Power Distribution Grids

Increase in the proliferation of distributed energy resources require real-time situational awareness for efficient grid operations. State estimation plays an important role for the real-time control and management of the power grid. As the sensing infrastructure grows, aggregating and handling high volumes of data at a centralized location is extremely difficult. To address this challenge, this paper first proposes a novel and efficient hier-archical spectral clustering-based network partitioning algorithm followed by a decentralized compressive sensing (DCS)-based state estimation. The applicability of the proposed network partitioning algorithm is tested on an IEEE 123-bus network, an IEEE 8,500-node system, and a 6,000+ node distribution network. The results shows that the proposed approach efficiently divides the network into multiple sub-networks with the minimum number of edge connections among the neighbors. Then, we perform DCS-based state estimation on the 6,000+ node distribution network after dividing the network into 18 optimal partitions. Simulation results show that the DCS-based state estimation recovers the system states with high accuracy and low complexity.

alternating direction method of multipliers↗