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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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Technology transfer is defined along with reasons for attempting to transfer technology. Topics discussed include theoretical models, stages of the innovation model, communication process model, behavior of industrial organizations, problem identification, technology search and match, establishment of a market mechanism, applications engineering, commercialization, and management of technology transfer.
The object-oriented data model is the culmination of over thirty years of database research. Initially, database research focused on the need to provide information in a consistent and efficient manner to the business community. Early data models such as the hierarchical model and the network model met the goal of consistent and efficient access to data and were substantial improvements over simple file mechanisms for storing and accessing data. However, these models required highly skilled programmers to provide access to the data. Consequently, in the early 70's E.F. Codd, an IBM research computer scientists, proposed a new data model based on the simple mathematical notion of the relation. This model is known as the Relational Model. In the relational model, data is represented in flat tables (or relations) which have no physical or internal links between them. The simplicity of this model fostered the development of powerful but relatively simple query languages that now made data directly accessible to the general database user. Except for large, multi-user database systems, a database professional was in general no longer necessary. Database professionals found that traditional data in the form of character data, dates, and numeric data were easily represented and managed via the relational model. Commercial relational database management systems proliferated and performance of relational databases improved dramatically. However, there was a growing community of potential database users whose needs were not met by the relational model. These users needed to store data with data types not available in the relational model and who required a far richer modelling environment than that provided by the relational model. Indeed, the complexity of the objects to be represented in the model mandated a new approach to database technology. The Object-Oriented Model was the result.
Climate change will profoundly impact Earth's environmental health as well as the world's economic and geopolitical landscape over the coming decades. The impacts of climate change are, in fact, already beginning to be experienced and have the potential to affect every living plant and animal on Earth within decades. Given this reality, every citizen of this planet should have the right to knowledge about the Earth's climate system and have the option to adapt to, or help mitigate the profound changes that are coming. In addition, a portion of the workforce needs to be capable of interpreting and analyzing climate information because, since the impacts of climate change will be widespread, pervasive, and continue to change over time, more professions will be interacting with climate data. We are already at, or past, the point where educators and their students require access to the scientific and technological resources - computer models, data, and visualization tools - that scientists use daily in the study of climate change. Although scientists use many methods to study Earth's climate system, global climate models (GCMs) have become the primary tools for exploring the complex interactions between components of the entire system: atmosphere, oceans, and land. GCMs are used to make projections of future climate change, to simulate climates of the past, and even to help scientists look for life on other planets. Like any model, a GCM can help people evaluate actions before they are taken. Like Business Intelligence software, they are Climate Intelligence tools. Unfortunately, GCMs are black boxes to most people. A previous chapter in this book by Gary Russell, entitled Building a Climate Model, is one example of the growing body of literature aimed at the general public describing the inner workings of global climate models. This literature goes a long way toward explaining climate model fundamentals. However, it will not be enough to alleviate their black-box nature unless people are afforded hands-on, authentic learning experiences as well.
While real-time simulation of Quantum Chromodynamics remains technologically out of reach, simplified models for studying elements of QCD phenomenology abound. This work presents a simple model, a spin-1 truncation of the Compact Abelian Higgs Model simulated on qutrit sites, in which confinement and string breaking is accessible to current simulation methods. In the low-energy regime of 1+1D scalar electrodynamics, the heavy modes are integrated out, producing a spin chain effective Hamiltonian in which Gauss' law is implicitly satisfied. We study the spectrum of string-like excitations using DMRG methods on the order of 100 sites. We demonstrate that an added, local chemical potential, playing a role analogous to external charges, permits parameter-dependent measurements of physical features of interest like the string tension and effective meson mass. Varying the chemical potential also permits a characterization of string stability not assessed in prior studies of confining lattice models.
NASA is committed to finding innovative solutions that improve the operational performance of ground support equipment while providing environment and cost benefits, as well. Through the Hydrogen Fuel Cell Mobile Lighting Tower (HFCML) project, NASA gained operational exposure to a novel application of high efficiency technologies. Traditionally, outdoor lighting and auxiliary power at security gates, launch viewing sites, fallback areas, outage support, and special events is provided by diesel generators with metal halide lights. Diesel generators inherently contribute to C02, NOx, particulate emissions, and are very noisy. In 2010, engineers from NASA's Technology Evaluation for Environmental Risk Mitigation Principal Center (TEERM) introduced KSC operations to a novel technology for outdoor lighting needs. Developed by a team led by Sandia National Laboratory (SNL), the technology pairs a 5kW hydrogen fuel cell with robust high efficiency plasma lights in a towable trailer. Increased efficiency, in both the fuel cell power source and lighting load, yields longer run times between fueling operations while providing greater auxiliary power. Because of the unit's quiet operation and no exhaust fumes, it is capable of being used indoors and in emergency situations, and meets the needs of all other operational roles for metal halide/diesel generators. The only discharge is some water and warm air. Environmental benefits include elimination of diesel particulate emissions and estimated 73% greenhouse gas emissions savings when the hydrogen source is natural gas (per GREET model). As the technology matures the costs could become competitive for the fuel cell units which are approximately 5 times diesel units. Initial operational . concerns included the hydrogen storage tanks and valves, lightning safety/grounding, and required operating and refueling procedures. TEERM facilitated technical information exchange (design drawings, technical standards, and operations manuals) necessary for KSC hydrogen system experts to approve use of the HFCML unit, including initiating the environmental checklist (i.e. exterior lighting waiver due to sea turtles), and development of operations and maintenance instructions. TEERM worked with SNL to establish a bailment agreement for KSC to utilize a Beta unit as part of normal Center Operations for a period of twelve months.
“Learn-to-Fly” (L2F) is an advanced technology development effort within the Modeling and Control for Agile Aircraft Development (MCAAD) group, a part of the NASA Transformative Aeronautics Concepts Program’s (TACP) Transformational Tools and Technologies (TTT) project. The goal of L2F is to develop technologies for enabling self-learning flight vehicles, using both ground- and flight-test approaches. Specifically, research has been conducted to demonstrate the potential to merge two enabling technologies, real-time aerodynamic modeling and adaptive flight controls, to substantially reduce the typical ground- and flight-testing time requirements for air vehicle design. This effort involved development of real-time, on-board algorithms to demonstrate key L2F technologies including aerodynamic modeling and control for an aircraft with minimal a priori knowledge. This research included both ground-based wind tunnel experiments utilizing modern design of experiments (DOE) techniques, as well as a flight test campaign, and was intended to rapidly advance these technologies and demonstrate key capabilities of the L2F approach. This paper presents the overview of the methods used to develop L2F technologies in NASA Langley Research Center’s 12-Foot Low Speed Tunnel, as well as in flight experiments. These methods include efficient wind tunnel data collection, real-time global nonlinear aerodynamic modeling in both the time and frequency domains, and the integration of the modeling techniques with adaptive flight controls, all of which were demonstrated using experimental validation.
Most remaining Department of Energy (DOE) sites will require extended periods of institutional control, especially at complex groundwater sites where attenuation-based strategies have been implemented to facilitate closure. The current practice of monitoring—obtaining and analyzing contaminant concentration in groundwater samples at numerous wells—will account for a large portion of the projected life-cycle at these DOE sites unless a new approach is adopted. State-of-the-art technologies are being developed, including in situ sensors, geophysics, radiation mapping, numerical modeling and AI/ML. These technologies can optimize monitoring strategies in space and time, provide spatially extensive information at vulnerable regions and/or provide more continuous monitoring at lower cost. As part of DOE’s Office of Environmental Management (DOE-EM’s) efforts to advance long-term monitoring systems, an in-person/virtual hybrid workshop was hosted by Savannah River National Laboratory (SRNL) on January 24 and 25, 2023, in Augusta, Georgia. Because DOE-EM’s complex sites will eventually be transferred to DOE’s Office of Legacy Management (DOE-LM), representatives of DOE-LM were important participants in the workshop. The purpose of the workshop was to identify challenges and opportunities for deploying advanced technologies for long-term monitoring at DOE sites. The key questions during the workshop were: 1) the regulatory acceptance of replacing a process that traditionally has used laboratory sampling and analysis of groundwater samples, and 2) the application of this strategy to the southwestern arid sites that include many of the remaining DOE-EM and DOE-LM complex groundwater plumes. Characteristics common to most arid sites present both limitations and opportunities for advanced technologies. DOE-EM has funded a National Laboratory team from SRNL, Lawrence Berkeley National Laboratory (LBNL), and Pacific Northwest National Laboratory (PNNL) to establish the overarching framework of long-term monitoring by systematically combining advanced hardware and software technologies. This project is titled “Advanced Long-Term Environmental Monitoring Systems (ALTEMIS)” and is sponsored by the DOE-EM Technology Development Program. The multi-laboratory team is currently developing and testing innovative monitoring strategies, including the use of in situ groundwater sensors, geophysics, drone/satellite-based remote sensing, reactive transport modeling, and artificial intelligence/machine learning (AI/ML). The project’s demonstration testbed is at the Savannah River Site (SRS) F-Area Seepage Basins, where a well-characterized complex groundwater plume composed of uranium and other radionuclides is in the latter stages of remediation. The workshop included more than 70 participants, presentations, a field visit to F-Area, breakout working groups, and large group discussion. Participants developed recommendations on five topics: in situ sensors, spatially integrative tools, challenges to regulatory acceptance, AI/ML strategies, and transitioning sites to DOE-LM.
The ASC Advanced Technology Development and Mitigation (ATDM) sub-program was established in 2014 to develop new simulation tools operating on exascale-class computers to serve NNSA (see Appendix B). Over the course of ATDM, LANL management have set a strategy for exascale-class application codes that follows two supportive and mutually risk-mitigating paths: evolution for established production integrated design codes (IDCs) – with a strong pedigree within the user community – based upon existing programming paradigms(MPI+X); and a new start ATDM project, Ristra, a high-risk/high-reward push for a next-generation multi-physics, multi-scale simulation toolkit based on emerging advanced programming systems(with an initial focus on data-flow task-based models exemplified by Legion). The role of Ristra as the high-risk/high-reward path for LANL’s codes was fully consistent with the goals of ATDM as described in Appendix B, in particular its emphasis on evolving ASC capabilities through novel computing programming models and computing technologies.
Innovations improve technology costs through various kinds of engineering advancements, including changes to materials choices and device or process designs. Understanding how these innovations relate to cost change can reveal aspects of the process of technology evolution, yet developing such understanding is often not possible with a strictly quantitative approach due to data limitations. In this paper we develop a hybrid quantitative-qualitative framework for relating specific innovations to cost change by using the variables in a quantitative technology cost change model as an organizing principle. We demonstrate this framework by applying it to the cost decline in photovoltaic (PV) systems over the last five decades. This framework generates new understanding of a set of innovations that contributed to PV modules’ sustained cost decline and the more modest trends observed in balance-of-system (BOS) costs. The results show the great diversity of innovations that affected PV costs, drawing on wide-ranging fields of expertise within scientific research and practice. We find that there are differences in the characteristics of innovations that reduced the cost of PV modules compared to innovations influencing BOS costs. Numerous module innovations reduced costs by advancing manufacturing tools and processes that improved material quality. Many BOS innovations reduced costs through a combination of component design changes, integration, automation, digitalization, and standardization. Overall, most innovations in our sample affected PV hardware. However, some also target ‘soft technologies’ such as task durations through innovations like fast-track permitting, which require improved collaboration and process streamlining. This framework also provides insight into the nature of knowledge spillovers between technologies. Both module and BOS hardware innovations show the benefits of PV’s position within an ‘ecosystem’ of continuously advancing technologies in many industries, in particular semiconductors and electronics, and also point to the importance of public institutions for accelerating testing, permitting, and training.
Today’s transportation is quickly transforming with the nascent advent of connectivity, automation, shared-mobility, and electrification. These technologies will not only affect our safety and mobility, but also our energy consumption, and environment. As a result, it is of unprecedented importance to understand the overall system impacts due to the introduction of these emerging technologies and concepts. Existing modeling tools are not able to effectively capture the implications of these technologies, not to mention accurately and reliably evaluating their effectiveness with a reasonable scope. To address these gaps, a dynamometer-in-the-loop (DiL) development and testing approach is proposed which integrates test vehicle(s), chassis dynamometer, and high fidelity traffic simulation tools, in order to achieve a balance between the model accuracy and scalability of environmental analysis for the next generation of transportation systems. With this DiL platform, a connected eco-operation system for the plug-in hybrid electric bus (PHEB) has been developed and tested, which can optimize the vehicle dynamics (and potentially powertrain control via smart energy management) to reduce the operational energy consumption as well as tailpipe emissions of the target PHEB. The system performance has been evaluated on the DiL platform with respect to a variety of traffic congestion levels. The results have shown that the developed system can save fuel by more than 13% while reducing the electricity consumption by 2% in the test scenarios.
A model has been developed for NASA to quantitatively compare and select life support systems and technology options. The model consists of a modular, top-down hierarchical breakdown of the life support system into subsystems, and further breakdown of subsystems into functional elements representing individual processing technologies. This paper includes the technology trades for a Mars mission, using solid waste treatment technologies to recover water from selected liquid and solid waste streams. Technologies include freeze drying, thermal drying, wet oxidation, combustion, and supercritical-water oxidation. The use of these technologies does not have any significant advantages with respect to weight; however, significant power penalties are incurred. A benefit is the ability to convert hazardous waste into a useful resource, namely water.
The costs of solar photovoltaics (PV) have been dropping in recent years, leading to increasing installations of solar PV systems and growing interest in how the technology will impact the electric grid at higher penetrations. Additionally, as battery costs decline it becomes important to understand the benefits and limitations of battery storage for the grid as well as potential benefits of co-locating battery storage and PV, particularly within the realm of future system planning. However, it is non-trivial to capture these potential benefits within a linearized capacity expansion model (CEM). This paper presents methodological developments to more fully represent the value and limitations of coupled PV and battery systems (PV + Battery) in CEMs using the Resource Planning Model (RPM), which co-optimizes capacity investments, transmission investments, and reduced-order dispatch in the Western Interconnection of North America through 2045. We use the model to simulate the evolution of the generation and transmission system under two core scenarios - a baseline scenario and a high renewable penetration scenario - coupled with sensitivities assuming low and midline PV and battery cost projections. When incorporating PV + battery, we find that it is important for CEMs to capture the ability of the coupled technology to provide firm capacity and reduce expected curtailment, compared to independent systems. These interactions can have even more dramatic impacts at higher solar penetrations.
The Side-by-Side (SBS) Hybrid is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This paper presents a dynamic model of the SBS Hybrid powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). The model consists of the rotors, electrical power system, and turboshaft engines connected through freewheeling clutches, gearboxes, and multiple shafts. This research effort models the complex behavior of the powertrain, including the operation of the freewheeling clutches and electrical power system at the simulation time scale of the shaft dynamics. Several simulations highlight the key features present in the model and demonstrate its operation.
The Side-by-Side (SBS) Hybrid is one of several Revolutionary Vertical Lift Technology (RVLT) concept aircraft identified by NASA to investigate Urban Air Mobility (UAM) requirements. This paper presents a dynamic model of the SBS Hybrid powertrain built using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) and the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). The model consists of the rotors, electrical power system, and turboshaft engines connected through freewheeling clutches, gearboxes, and multiple shafts. This research effort models the complex behavior of the powertrain, including the operation of the freewheeling clutches and electrical power system at the simulation time scale of the shaft dynamics. Several simulations highlight the key features present in the model and demonstrate its operation.
As part of the NASA Vehicle Systems Safety Technologies (VSST), Assuring Safe and Effective Aircraft Control Under Hazardous Conditions (Technical Challenge #3), an effort is underway within Boeing Research and Technology (BR&T) to address Advanced Modeling and Uncertainty Quantification for Flight Dynamics (VSST1-7). The scope of the effort is to develop and evaluate advanced multidisciplinary flight dynamics modeling techniques, including integrated uncertainties, to facilitate higher fidelity response characterization of current and future aircraft configurations approaching and during loss-of-control conditions. This approach is to incorporate multiple flight dynamics modeling methods for aerodynamics, structures, and propulsion, including experimental, computational, and analytical. Also to be included are techniques for data integration and uncertainty characterization and quantification. This research shall introduce new and updated multidisciplinary modeling and simulation technologies designed to improve the ability to characterize airplane response in off-nominal flight conditions. The research shall also introduce new techniques for uncertainty modeling that will provide a unified database model comprised of multiple sources, as well as an uncertainty bounds database for each data source such that a full vehicle uncertainty analysis is possible even when approaching or beyond Loss of Control boundaries. Methodologies developed as part of this research shall be instrumental in predicting and mitigating loss of control precursors and events directly linked to causal and contributing factors, such as stall, failures, damage, or icing. The tasks will include utilizing the BR&T Water Tunnel to collect static and dynamic data to be compared to the GTM extended WT database, characterizing flight dynamics in off-nominal conditions, developing tools for structural load estimation under dynamic conditions, devising methods for integrating various modeling elements into a real-time simulation capability, generating techniques for uncertainty modeling that draw data from multiple modeling sources, and providing a unified database model that includes nominal plus increments for each flight condition. This paper presents status of testing in the BR&T water tunnel and analysis of the resulting data and efforts to characterize these data using alternative modeling methods. Program challenges and issues are also presented.
A recent National Academies consensus report addresses monitoring and assessment of cumulative effects of large-scale and multiple restoration projects within the context of long-term environmental change. Fines and penalties from the Deepwater Horizon oil spill in the Gulf of Mexico (GoM) have supported hundreds of restoration projects at spatial scales not often possible in the past. Here, in this paper, the report committee members and staff provide personal reflections from our time working on the study. We found that gaps in data collection, issues with data accessibility, and a lack of synthesis and analysis are hindering the ability to answer a basic question: What are the impacts of these many restoration efforts on improving ecosystem health and productivity in the GoM at the regional and Gulf wide scale? Restoration efforts are occurring in environments where many trends are changing and exhibiting higher variability than in the past, suggesting that previously successful restoration practices may no longer be adequate to compensate for the effects of environmental changes and variability. Our proposed approach to these challenges includes employing emerging monitoring technologies; using conceptual models; devising an adaptive management framework; rethinking restoration outcome goals; assessing cumulative effects; and undertaking rigorous synthesis and analysis of existing information on long-term environmental trends and restoration efforts. Restoration scientists and practitioners working in the GoM have an unprecedented opportunity to demonstrate large-scale environmental recovery if advances in monitoring, synthesis, assessment, and action are taken quickly. We are cautiously optimistic that, with mid-course adjustments, continued progress toward large-scale environmental recovery is possible.
Using Python-based geospatial analytics, open-source web mapping technologies, geophysical data models, and subsurface stratigraphy models from the Regional Geology Geologic Framework Model database assembled by Los Alamos National Laboratory, we developed a suite of web-based geologic investigation tools to identify and understand subsurface structures and geophysical properties concerning salt and shale formations within the contiguous United States. Coupled with a web map interface, these tools allow for the interactive visualization of various geologic data and demonstrate the ability to quickly generate custom subsurface cross-sections, borehole charts, and diagrams for azimuthal orientation data. These capabilities were developed for stakeholder and researcher use to facilitate informed decision making for spent nuclear waste disposition. However, these capabilities provide a flexible model for a variety of subsurface investigation needs, and we have demonstrated this flexibility by adapting these tools to meet visualization needs for various subsurface models within a web-based platform.
This Front-End Engineering Design (FEED) was funded by the U.S. Department of Energy (DOE) to estimate the cost to capture and compress 90% of the CO 2 from an existing natural gas combined cycle (NGCC) in Denver City, Texas, USA. The FEED used the PZAS (Piperazine with the Advanced Stripper) 2G amine scrubbing technology developed and modeled by The University of Texas at Austin. This FEED is unique in providing more public cost details than other FEEDs funded by DOE. The primary objective of the FEED was to provide a comprehensive estimate for the total installed cost of the capture plant. The estimated capital cost of NGCC at the Mustang Station is $\$727$ million for a capacity of 460 MW and 1.6 million tonnes CO 2 /yr. This includes a contingency of $\$104.6$ million and a contractor’s profit of $\$60.1$ million. The total direct field cost is $\$384.1$ million. With an optimistic fuel value of $\$3$/MMBtu, the estimated cost of capture varies from $\$85$/t at 4% IRR/85% load to $\$170$/t at 10% IRR/52% load. Air cooling is technically feasible but expensive. The air cooling systems for the water wash and pump-around intercooling account for 23.4% of the direct cost. The gas-fired boilers represent only 4% of the direct costs, but steam extraction would reduce energy cost, free up cooling water, and reduce the direct costs of processing additional flue gas and CO 2 from the boilers. The absorbers represent 9.6% of the direct cost in this FEED with no direct contact cooler and only 7.6 m of packing. Furthermore, the solvent cross exchangers are less expensive than expected (2.5% of direct costs). Doubling the number of these exchangers could reduce the heat duty from 3.0 to 2.5 GJ/t CO 2 .