Search NASA⌕ Search

SEARCH · Search NASA

Results for “Project Management”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Smart CO2 Transport-Route Planning Tool: Providing Data and Insights for Accelerating Carbon Transport & Storage Deployment

Overview presentation given at the 2024 FECM / NETL Carbon Management Research Project Review Meeting on NETL's Bipartisan Infrastructure Law-funded Smart CO2 Transport-Route Planning Tool and associated geodatabase. This machine learning informed, data-driven public resource was designed to inform regulators, industry, and researchers plan and develop safe and efficient transport routes across the country.

Romeo, Lucy↗
DOE OSTI2024

Framework for Optimization, Quantification of Uncertainty, and Surrogates, and CCSI2 Toolset Capabilities

This poster will present key features and capabilities of the CCSI2 software platform to relevant technical and research audience members at the 2024 FECM / NETL Carbon Management Research Project Review Meeting. Attendees will learn about available process models in the CCSI2 Toolset, as well as design of experiments and machine learning features in the Framework for Optimization, Quantification of Uncertainty, and Surrogates (FOQUS) software to support pilot plant work.

Paul, Brandon↗
DOE OSTI2024

Overview of the FECM/NETL CO2 Transport Cost Model (CO2_T_COM)

This presentation provides an overview of the FECM/NETL CO2 Transport Cost Model (CO2_T_COM). COP2_T_COM is a technoeconomic model of a point-to-point pipeline transporting liquid CO2. There can be booster pumps along the pipeline. Presented at the 2024 FECM - NETL Carbon Management Research Project Review Meeting, 5-9 August, 2024, Pittsburgh, PA.

Morgan, David↗
DOE OSTI2024

Colorado (Pueblo) Regional DAC Hub

Presentation about the Colorado (Pueblo) Regional DAC Hub given to attendees of the 2024 FECM/NETL Carbon Management Research Project Review Meeting.

42 ENGINEERING↗
DOE OSTI2026

Generation of Rare Earth Metals from Rare Earth Oxide Using Microwave Plasmas

The overarching goal of the proposed project is to develop a simple, energy-saving, high-selectivity technology for efficiently converting rare-earth oxides (REOs) to rare-earth metals (RE-metals) using microwave plasma under low temperature and inexpensive H 2 and N 2 . The project was managed and led by Dr. Maohong Fan at the University of Wyoming. The collaborating institutions include Ames Lab and Colorado School of Mines. The industrial collaboration entity is Eutectix, LLC. The use of hydrogen to reduce rare earth oxides has many advantages, as it is renewable and does not produce harmful emissions during metal production. Also, it avoids the use of carbon and the emission of CO 2 . Nd 2 O 3 treated with hydrogen plasma shows new peaks alongside those of Nd 2 O 3 . Some of these peaks are close to (28.4, 29.4, 30.5, 32.3, 36.6, 42.1, 48.9, 50.08, 55.1, 59.05, 59.64, 60.68, 62.5, 63.25), which may be related to elemental Nd.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Connected and Learning Based Optimal Freight Management for Efficiency

The management of the future heterogenous fleet is a complex decision-making problem. The heterogenous fleet is emerging as decarbonization technologies are deployed by fleets toward lowering the freight operation emissions in Medium and Heavy-duty vehicles. Traditionally, in fleets characterized by a homogeneous Diesel Internal Combustion Engine (ICE) powertrain, the process of fleet planning and operational optimization unfolds sequentially without the necessity to account for powertrain and vehicle-specific characteristics during dispatch decisions. Fleets with trucks less than 5 years old tend to maintain stable vehicle efficiency with minimal operational reliability risks for fleet managers. However, the landscape changes with the incorporation of emerging powertrain technologies, which lack extensive operational data and service experiences. This includes technologies like hybrid, Electric, Fuel Cell, or alternative fuel ICE. Operational decisions for fleets featuring heterogeneous powertrain technologies and facing limited access to alternative fueling and charging stations become intricate, requiring careful consideration and optimization at each dispatch. The difference in efficiency characteristics of emerging technologies, their range limitations, and the restricted availability of charging/alternative fueling infrastructure, coupled with sensitivity to driving conditions (e.g., EV range reduction in low temperatures) and their impact on component aging (such as batteries), become pivotal factors influencing the reliable and efficient freight transportation. To make the path toward low emission freight transportation efficient and reliable, an AI-assisted fleet management software is developed in this project to help fleet managers in optimizing both adoption of emerging powertrain decarbonization, connected and automated technologies and also operating the fleet after such technologies are deployed as schematically. Freight transportation requirements are different depending on the cargos to be shipped, customer requirements and regions of operations. This further highlights the need for software and digital solutions to tailor deployment and operation of emerging powertrain, connectivity, and automation technologies toward the specific fleet operation requirements. The fleet management optimizer was also integrated with a model of the fleet to simulate the operation of the fleet over 1 year of the baseline fleet operation (250,000+ shipments) indicating the significance of day-to-day variations on emissions and energy consumption of a freight transportation fleet. The results demonstrate ≥20% improvement in freight efficiency in terms of WTW CO2 per ton-mile of cargo shipments while all fleet operation constraints are enforced, and the cost (CapEx and OpEx) is minimized.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Design of the ECCE detector for the Electron Ion Collider

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. Finally, this detector concept has been selected to be the basis for the EIC project detector.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

MARVEL Technical Overview: Breakdown of cost and scope growth through 90% Final Design

This report presents a breakdown of cost and scope growth for the Microreactor Applications Research Validation and Evaluation (MARVEL) project through the design phase, and includes observations, lessons learned, and the results from an independent project assessment. It presents the status and history of the project. Technology maturity is considered in high-level, qualitative comparison to other microreactor design efforts. Its purpose is to record MARVEL’s evolution and lessons learned from the planning and design phases through completion of 90% final design. Analyses included a detailed review of project cost, schedule, and periodic project reports and management documents. The Primary Coolant Apparatus Test (PCAT) is specifically highlighted. It was concluded that MARVEL would have benefited from more extensive planning early in the project to better define cost and schedule to provide more certainty in the total project cost and delivery date. Modest cost and schedule improvements may have been possible, but compared qualitatively, MARVEL’s total cost and schedule performance are consistent with that of other efforts currently underway. Better planning would have provided more certainty, improved risk mitigations, and potentially eliminated delays due to funding shortfalls. A recommended path forward is presented that addresses recommendations in the independent project assessment.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Real Time-Optimal Power Flow-Based Distributed Energy Resource Management System (DERMS)

This project aims to promote lab-proven clean energy technology to commercially scalable versions of the technology, integrate the technology with broader systems, provide extended performance data, and validate the manufacturability and reliability of the technology. The lab-proven technology, RT-OPF DERMS, was developed and validated through previous U.S. Department of Energy-funded efforts, including Advanced Research Projects Agency-Energy funding under the Network Optimized Distributed Energy Systems program and Holy-Cross Energy High Impact Project. In the Advanced Research Projects Agency-Energy Network Optimized Distributed Energy Systems project, the RT-OPF DERMS was developed and implemented in multiple hardware platforms, demonstrating its performance and capabilities in the lab and field environments. The technology was also evaluated and matured via a participation in the U.S. Department of Energy I-Corps program, whose goal is to pair teams of researchers with industry mentors for an intensive 2-month training in which the researchers define technology value propositions, conduct customer discovery interviews, and develop viable market pathways for their technologies. These activities indicate the high technology maturity and Technology Readiness Level of the RT-OPF DERMS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Pipeline for Integrated Projects in Energy Systems (PIPES): A Tool for Integrated System Planning [Slides]

The Pipeline for Integrated Projects in Energy Systems (PIPES) is a comprehensive project, data, and workflow management tool designed for integrated modeling teams. PIPES facilitates the management of data requirements, tasks, and progress tracking, serving as a higher-level integration layer that works across various data and modeling software. This tool integrates models, data, and tools to perform large-scale, integrated analysis work at scale. PIPES is designed to streamline integrated modeling projects, enhance collaboration, and ensure the quality and efficiency of data management and workflow processes. This presentation introduces PIPES a multi-model tool for integrated system planning; it describes the underlying architecture, deep dives into common user workflows, and outlines the upcoming development roadmap beyond its current alpha state.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Energy-Efficient Direct Air Capture System for High Purity CO 2 Separation

The primary objective of this project is to demonstrate the University of Cincinnati’s direct air capture (DAC) sorbent technology in a monolithic structure installed in a passive air contactor (PAC). The modified amine-based sorbent technology provides reduced heat of desorption and resistance to thermal and oxidative degradations for robust and long-term performances and cost effective sorbent management. During the project period, additional amine modifications were developed and a U.S./PCT patent application was filed.

42 ENGINEERING↗
DOE OSTI2026

Gateway Cities Unplugged: (em)Powering Affordable Housing (Final Technical Report)

The Gateway Cities Unplugged: (em)Powering Affordable Housing (the “Project”) was launched to address a critical challenge in the U.S. building and energy sectors: enabling multifamily buildings especially those serving low and moderate‑income (LMI) communities to actively support grid modernization through Grid‑Interactive Efficient Buildings (GEB). Multifamily housing represents a large share of national building energy consumption, yet the sector faces persistent barriers to adopting advanced load flexibility technologies, including capital constraints, aging infrastructure, and limited access to demand‑side management tools. This Project sought to overcome those barriers by defining, evaluating, and designing commercially viable GEB technology packages for six representative multifamily properties across Massachusetts, Connecticut, and New York.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

LLM Generation of Online Courses from a Curated Set of Documents in the Nuclear Safeguards Domain

A multidisciplinary team at Argonne National Laboratory explores the application of advanced technologies to enhance knowledge transfer and retention within the nuclear safeguards domain. Specifically, it examines the feasibility of leveraging secure large language models (LLMs) to streamline the creation of e-learning modules for the U.S. National Nuclear Security Administration (NNSA) Office of International Nuclear Safeguards (NA-241). The initiative addresses the critical need for preserving institutional memory and accelerating skill development amidst the imminent retirement of senior professionals in the field in addition to supporting good knowledge management practices. The project integrates instructional design theory with cutting-edge AI technologies to transform curated document sets from the Safeguards Knowledge Repository (SKR) into modular online courses. By automating the generation of learning objectives and instructional content, the effort aims to reduce manual effort while maintaining high-quality educational outcomes. A limited measure of human supervision, however, ensures accuracy, relevance, and alignment with NNSA’s strategic priorities. Key findings highlight the potential of AI-assisted course generation to support safeguards professionals by creating structured, interactive learning experiences. The report underscores the importance of SME validation to address limitations in AI-generated content, such as terminology errors and gaps in coverage. Recommendations include adopting a structured workflow combining LLM acceleration with expert oversight to ensure accuracy, usability, and alignment with learner needs. This work demonstrates Argonne’s commitment to advancing national security and scientific excellence through innovative knowledge management solutions.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Synthetic Biology of Plants and Microbes for Agriculture, Environment, and Future Applications

Agriculture is under pressure to provide food for a growing population and the feedstock required to drive the bioeconomy. Methods to breed and genetically modify plants are inadequate to keep pace. When engineering crops, traits are painstakingly introduced into plants one-at-a-time, combine unpredictably, and are continuously expressed. Synthetic biology is changing these paradigms with new genome construction tools, computer aided design (CAD), and artificial intelligence (AI). “Smart plants” contain circuits that respond to environmental change, alter morphology, or respond to threats. Further, the plant and associated microbes (fungi, bacteria, archaea) are now being viewed by genetic engineers as a holistic system. Historically, plant health has been enhanced by many natural and laboratory-evolved soil microbes marketed to enhance growth, provide nutrients, or confer pest/stress resistance. Synthetic biology has expanded the number of species that can be engineered, increased the complexity of engineered functions, controlled environmental release, and assembled stable consortia. New CAD tools will manage genetic engineering projects spanning multiple plant genomes (nucleus, chloroplast, mitochondrion) and the thousands of genomes of associated bacteria/fungi. Here, this review covers advanced genetic engineering techniques to drive the next agricultural revolution, as well as push plant engineering into new realms for manufacturing, infrastructure, sensing, and remediation.

Clauer, Phillip [Massachusetts Inst. of Technology↗
DOE OSTI2025

Role of Forest Carbon Change in Shaping Future Land Use and Land Cover Change

Global change, particularly the changes in atmospheric CO 2 concentration, climatic variables, and nitrogen deposition, has been widely recognized and examined to have worldwide impacts on forest carbon. However, its influence on forest area required to meet the demand for timber and carbon storage and subsequent land use and land cover change (LULCC) is rarely studied. This study explores the role of global change-driven forest carbon change in shaping future global LULCC projections and investigates underlying drivers. We incorporated the global change impacts on forest carbon from the Canadian Land Surface Scheme Including Biogeochemical Cycles model simulations (driven by meteorological forcing projections from two Earth system models [ESMs]) into the Global Change Analysis Model, under three combinations of shared socioeconomic pathways and representative concentration pathways (SSP126, SSP370, and SSP585). Including forest carbon change decreases the projected expansion of managed forest and managed pasture, reduces the loss of unmanaged pastures and forests, and provides more cropland. The relative change in managed forest by 2100 is -4.0%, -21.7%, and -31.9%, under SSP126, SSP370, and SSP585, respectively, when forest carbon change is considered. CO 2 fertilization is the dominant driver, increasing forest vegetation and soil carbon by 37% and 4.1%, and leading to 78.6% of the total area with a change in land use types by 2100 under SSP585. In comparison, climate change reduces forest vegetation and soil carbon by -3.5% and -0.8%, influencing 23.9% of the total area with a change in land use types by 2100 under SSP585, while nitrogen deposition has minor impacts. Using meteorological forcing data from two ESMs leads to similar impacts of forest carbon change on LULCC in terms of sign and trend but different magnitudes. This study highlights the large impact of forest carbon change on shaping future LULCC dynamics and the critical role of CO 2 fertilization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data Acquisition and Control for Marine Energy Devices: Cost Considerations

This document discusses the process involved with developing a data acquisition system specifically in the context of applications for Marine Renewable Energy (MRE) technologies however, much of what is presented is applicable to applications requiring data acquisition in general. The detail on the process is provided to highlight the critical steps and needs for a successful measurement campaign and to understand what can impact the overall outcome, cost, and schedule. The process presented is an amalgamation of best practices, lessons learned, recommendations, and prudent technical project planning and management. Data acquisition systems may be tightly integrated with or into the device under measurement and it often has its own dependencies that must be met. Therefore, early consideration and planning for the data acquisition system are stressed throughout this document.

13 HYDRO ENERGY↗
DOE OSTI2025

An Early Investigation of the HHL Quantum Linear Solver for Scientific Applications

In this paper, we explore using the Harrow–Hassidim–Lloyd (HHL) algorithm to address scientific and engineering problems through quantum computing, utilizing the NWQSim simulation package on a high-performance computing platform. Focusing on domains such as power-grid management and climate projection, we demonstrate the correlations of the accuracy of quantum phase estimation, along with various properties of coefficient matrices, on the final solution and quantum resource cost in iterative and non-iterative numerical methods such as the Newton–Raphson method and finite difference method, as well as their impacts on quantum error correction costs using the Microsoft Azure Quantum resource estimator. We summarize the exponential resource cost from quantum phase estimation before and after quantum error correction and illustrate a potential way to reduce the demands on physical qubits. This work lays down a preliminary step for future investigations, urging a closer examination of quantum algorithms’ scalability and efficiency in domain applications.

hybrid software for QC-HPC↗