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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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Progress in the development of a performance optimized engine system design for an advanced LOX/hydrogen expander cycle engine is reported. Analysis of the components and engine and the resulting drawings is discussed. The status of the orbit transfer vehicle liquid engine transient simulation computer model is given.
NASA has responded to the increased emphases on cost-efficient operation of today's airline fleet with an ongoing research program to investigate the requirements and benefits of using new airborne guidance and pilot procedures designed to yield cost-optimal flight profiles that are compatible with advanced air traffic control system concepts. A trajectory optimization algorithm has been incorporated into one of NASA Langley's fixed-based simulators to investigate the pilot/cockpit interface requirements. The trajectories that are generated by this algorithm differ from conventional profiles in that they are constantly varying in both flight path angle and airspeed. Considering the dynamic nature of these profiles, conventional guidance may be insufficient for practical use. This paper summarizes the results of an initial set of piloted simulation tests to investigate the basic guidance requirements for flying the near-optimal trajectories.
Here this paper presents an overview on the application of CALPHAD (CALculation of Phase Diagrams) methodology in the design and development of advanced lightweight metallic materials including magnesium, aluminum, titanium, aluminum-based metal matrix composites, and high entropy alloys. In this work, CALPHAD methodology has been established and summarized from the construction of databases describing thermodynamics, atomic mobility, kinetics, thermo-physical properties (such as viscosity) to the application of computational design of lightweight materials. The examples in this paper have demonstrated the effectiveness and capability of CALPHAD methodology in accelerating the design of advanced lightweight materials by optimizing the compositions and various heat-treatment conditions, modifying the evolution of microstructures during processing, and finally predicting the mechanical properties (e.g., yield strength and hardness) of the lightweight components. Although the examples are given in lightweight alloys for structural applications, the fundamental methodology and modeling principles are applicable to all materials and engineering applications. Thus, the future of the advanced material design will be strongly based on development of CALPHAD methodology such as the construction of reliable databases coupled with CALPHAD-based models for various applications.
District energy systems have the potential to achieve deep energy savings by leveraging the density and diversity of loads in urban districts. However, planning and adoption of district thermal energy systems is hindered by the analytical burden and high infrastructure costs. It is hypothesized that network topology optimization would enable wider adoption of advanced (ambient temperature) district thermal energy systems, resulting in energy savings. In this study, energy modeling is used to compare the energy performance of “conventional” and “advanced” district thermal energy systems at the urban district level, and a partial exhaustive search is used to evaluate a heuristic for the topology optimization problem. For the prototypical district considered, advanced district thermal energy systems mated with low-exergy building heating and cooling systems achieved a source energy use intensity that was 49% lower than that of conventional systems. The minimal spanning tree heuristic was demonstrated to be effective for the network topology optimization problem in the context of a prototypical district, and contributes to mitigating the problem’s computational complexity. The work presented in this paper demonstrates the potential of advanced district thermal energy systems to achieve deep energy savings, and advances to addressing barriers to their adoption through topology optimization.
Training an effective deep learning model to learn ocean processes involves careful choices of various hyperparameters. We leverage DeepHyper’s advanced search algorithms for multiobjective optimization, streamlining the development of neural networks tailored for ocean modeling. The focus is on optimizing Fourier neural operators (FNOs), a data-driven model capable of simulating complex ocean behaviors. Selecting the correct model and tuning the hyperparameters are challenging tasks, requiring much effort to ensure model accuracy. DeepHyper allows efficient exploration of hyperparameters associated with data preprocessing, FNO architecture-related hyperparameters, and various model training strategies. We aim to obtain an optimal set of hyperparameters leading to the most performant model. Moreover, on top of the commonly used mean squared error for model training, we propose adopting the negative anomaly correlation coefficient as the additional loss term to improve model performance and investigate the potential trade-off between the two terms. The numerical experiments show that the optimal set of hyperparameters enhanced model performance in single timestepping forecasting and greatly exceeded the baseline configuration in the autoregressive rollout for long-horizon forecasting up to 30 days. Utilizing DeepHyper, we demonstrate an approach to enhance the use of FNO in ocean dynamics forecasting, offering a scalable solution with improved precision.
The Center for Understanding Subsurface Signals and Permeability is a new U.S. Department of Energy Earthshot Center focused on understanding and predicting the long-term evolution of permeability in enhanced geothermal systems. The center will use a highly instrumented testbed within the Sanford Underground Research Facility to conduct field scale experiments that elucidate and test capabilities to simulate geochemical-geomechanical interactions and permeability evolution. Here we demonstrate initial developments using previously collected electrical resistivity tomography (ERT) monitoring data with high-performance multi-physics modelling advancements to inform the optimal location of two new monitoring boreholes. Specifically, ERT monitoring data collected during shear stimulation testing shows marked responses to changes in stress during borehole pressurization. We demonstrate how the same response is being simulated, ultimately to train a machine-learning algorithm to estimate rock properties and enable enhanced prediction of stress and strain responses anticipated during future testing campaigns.
Computational methods underpin advancing the science and engineering of energy efficiency, sustainable transportation, renewable power technologies, and developing a knowledge base to optimize energy systems. Researchers with access to enough computing, and the right type, can focus their ingenuity and creativity on addressing the energy challenges. NREL’s advanced computing influence spans several common themes across the Office of Energy Efficiency and Renewable Energy (EERE), including materials discovery, process modeling, fluid dynamics, resource mapping, and analysis of large-scale systems with real-time optimization.
Even with the recent shift in focus of NASA’s human spaceflight program towards the Moon, the long-term goal continues to be crewed missions to Mars. Regardless of the accepted architecture, in-space transportation systems are a critical portion to achieving this goal. An emphasis is placed on presenting decision makers with many options early on to make an informed down-selection. Although current processes are able to address any aspects of the challenging underlying multi-disciplinary analysis and optimization problem of these advanced concepts, they are unable to comprehensively perform design space exploration inexpensively,potentially leaving attractive alternatives on the table. A design framework is proposed that is capable of enabling the integrated mission analysis, vehicle sizing and synthesis problem for in-space transportation architectures. This framework is enabled through the use of the vehicle synthesis tool, Dynamic Rocket Equation Tool, various subsystem sizing models, and low-thrust trajectory optimization codes. As a case study to demonstrate the framework, two design points of a hybrid propulsion stage concept, studied by Georgia Tech’s 2018 Revolutionary Aerospace Systems Concepts-Academic Linkage team, is explored.
Even with the recent shift in focus of NASA’s human spaceflight program towards the Moon, the long-term goal continues to be crewed missions to Mars. Regardless of the accepted architecture, in-space transportation systems are a critical portion to achieving this goal. An emphasis is placed on presenting decision makers with many options early on to make an informed down-selection. Although current processes are able to address any aspects of the challenging underlying multi-disciplinary analysis and optimization problem of these advanced concepts, they are unable to comprehensively perform design space exploration inexpensively, potentially leaving attractive alternatives on the table. A design framework is proposed that is capable of enabling the integrated mission analysis, vehicle sizing and synthesis problem for in-space transportation architectures. This framework is enabled through the use of the vehicle synthesis tool, Dynamic Rocket Equation Tool, various subsystem sizing models, and low-thrust trajectory optimization codes. As a case study to demonstrate the framework, two design points of a hybrid propulsion stage concept, studied by Georgia Tech’s 2018 Revolutionary Aerospace Systems Concepts-Academic Linkage team, is explored.
In this work, we study characteristics of 14-nm-gate InGaAs-based trigate MOSFET (metal-oxide-semiconductor field effect transistor) devices with a channel capping layer. The impacts of thickness and gallium (Ga) concentration of the channel capping layer on the device characteristic are firstly simulated and optimized by using three-dimensional quantum-mechanically corrected device simulation. Devices with In{sub 1−x}Ga{sub x}As/In{sub 0.53}Ga{sub 0.47}As channels have the large driving current owing to small energy band gap and low alloy scattering at the channel surface. By simultaneously considering various physical and switching properties, a 4-nm-thick In{sub 0.68}Ga{sub 0.32}As channel capping layer can be adopted for advanced applications. Under the optimized channel parameters, we further examine the effects of channel fin angle and the work-function fluctuation (WKF) resulting from nano-sized metal grains of NiSi gate on the characteristic degradation and variability. To maintain the device characteristics and achieve the minimal variation induced by WKF, the physical findings of this study indicate a critical channel fin angle of 85{sup o} is needed for the device with an averaged grain size of NiSi below 4x4 nm{sup 2}.
A select overview is provided of ongoing research focusing on the development and verification of integrated structural analysis and optimal design capabilities for advanced aerospace propulsion and power systems. Subjects discussed include the following: (1) Composites - analytical models (composite mechanics), integrated computational methods, and characterization of composite structural response and durability for resin-, metal-, and ceramic-matrix systems; (2) Advanced inelastic analysis - algorithm/numerical methods for more accurate and efficient analysis; (3) Constitutive modeling - theoretical formulation and characterization of thermoviscoplastic material behavior; (4) Computational simulation - engine structures from components to assembly, and up to an entire engine system subjected to simulated test-stand and mission load histories; (5) Probabilistic structural analysis - quantification of the effects of uncertainty in geometry, material, loads, and boundary conditions on structural response for true reliability assessment; and (6) Interdisciplinary optimization - incorporation of mathematical optimization and multidisciplinary analyses to provide streamlined, autonomous optimal design systems.
The performance of an advanced technology conceptual turbojet optimized for a high-speed civil aircraft is presented. This information represents an estimate of performance of a Mach 3 Brayton (gas turbine) cycle engine optimized for minimum fuel burned at supersonic cruise. This conceptual engine had no noise or environmental constraints imposed upon it. The purpose of this data is to define an upper boundary on the propulsion performance for a conceptual commercial Mach 3 transport design. A comparison is presented demonstrating the impact of the technology proposed for this conceptual engine on the weight and other characteristics of a proposed high-speed civil transport. This comparison indicates that the advanced technology turbojet described could reduce the gross weight of a hypothetical Mach 3 high-speed civil transport design from about 714,000 pounds to about 545,000 pounds. The aircraft with the baseline engine and the aircraft with the advanced technology engine are described.
Managing energy, water, and environmental priorities and constraints within a cascade hydropower system is a challenging multiobjective optimization effort that requires advanced modeling and forecasting tools. Within the mid-Columbia River system, there is currently a lack of specific solutions for predicting how coordinated operational decisions can mitigate the impacts of total dissolved gas (TDG) supersaturation while satisfying multiple additional policy and hydropower generation objectives. In this study, a reduced-order TDG uptake equation is developed that predicts tailrace TDG at seven hydropower facilities on the mid-Columbia River. The equation is incorporated into a general multiobjective river, reservoir, and hydropower optimization tool as a prioritized operating goal within a broader set of system-level objectives and constraints. A test case is presented to assess the response of TDG and hydropower generation when TDG supersaturation is optimized to remain under state water-quality standards. Satisfaction of TDG as an operating goal is highly dependent on whether constraints that limit TDG uptake are implemented at a higher priority than generation requests. According to the model, an opportunity exists to reduce TDG supersaturation and meet hydropower generation requirements by shifting spillway flows to different time periods. In conclusion, a coordinated effort between all project owners is required to implement systemwide optimized solutions that satisfy the operating policies of all stakeholders.
Optimal operation of lithium-ion batteries requires robust battery models for advanced battery management systems (ABMS). A nonlinear model predictive control strategy is proposed that directly employs the pseudo-two-dimensional (P2D) model for making predictions. Using robust and efficient model simulation algorithms developed previously, the computational time of the nonlinear model predictive control algorithm is quantified, and the ability to use such models for nonlinear model predictive control for ABMS is established.
Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.
NASA WorldWind: Open Source Visualization Technology for Earth Observation WorldWind, open source virtual globe technology for Java, iOS, Android and Web, is provided by NASA and is architected as API-centric modular componentry. This enable it to be continually optimized and feature-enriched in ways that allow applications based on this SDK (Software Development Kit) to benefit Earth Observation, especially Open Science, with minimal or no adjustment for the decade ahead. The next-generation National Airspace System (NAS) aviation management system for the U.S. Federal Aviation Administration, FAA, uses WorldWind, as do applications currently being developed by the European Space Agency, along with several other US and European government agencies and industry partners. This presentation will demonstrate several NASA open source use cases for WorldWind technology that include advances being made to optimize access to NetCDF and HDF data via WebWorldWind.NASA WorldWind: Multidimensional Geospatial Web Platform The ability to see spatial data in its native context is essential for that data to be appreciated whether by the scientific community, policy and decision-makers or the general public. Recently, the accessibility of spatial data has dramatically improved. Without the need to install an application, spatial data can now be experienced via any web browser, mobile devices included. For developers, by simply updating the app on your server, the latest version of your application is now immediately available to your entire usercommunity. Unlike other virtual globes such as Google Earth, NASA World Wind offers something very special, full control to customize the interface with any features or functionalities you might need. You decide how the data is accessed and experienced. This allows you to provide maximum value of the information to your user community. The web version of NASA WorldWind (WebWorldWind) has made it possible for a whole new suite of applications for managing and sharing spatial data. Apps built with this web version are ideal for immediate social media type activity and also facilitate delivery of sophisticated data exchange scenarios such as weather and climate research, disaster response, personal navigation, and industrial-strength tracking for transportation, supply chain, aviation and satellites. WebWorldWind is an application component, not an app in itself. It is written in JavaScript and provides the real world geographic context for spatial data and information visualization, using a rich set of shapes and graphic primitives. WebWorldWind also provides platform independence, while accommodating any number of data types. Web WorldWind runs on any platform via a browser, i.e., Internet Explorer, Firefox, Chrome and Safari. Features include, 3D virtual globe, 2D map with multiple projection choices (Mercator, Polar, UPS, Equirectangular), imagery and elevation import, extensible, data retrieval (via REST, WMS, WCS, WFS, Bing, User-Defined), decluttering, measurement, accurate line-ofsight, subsurface visualization, and more.
Simultaneously reducing criteria pollutants and fuel consumption is important for clean air and improving vehicle total cost of ownership. The goal of this effort was focused on a 90% NOx reduction and 10% fuel savings for an off-road 407 kW diesel engine. The baseline was a production Fiat Powertrain 13L engine and aftertreatment system meeting 0.4 g/kW-hr NOx. The baseline system was quantified over the NRTC, RMC, new low load cycle and five field cycles. A next generation engine was built incorporating several fuel-efficient design features, including a higher compression ratio, increased fuel-rail pressure, low-friction piston rings, and a high-efficiency variable-geometry turbocharger. Cylinder deactivation and EGR pump technologies were added to this engine as well. The combination was optimized prior to adding advanced aftertreatment systems, showing the trade-off of engine out NOx and exhaust temperature. Two next-generation catalyst technologies were employed into a LO-SCR plus main SCR system, both with and without an electric heater upstream of the LO-SCR. These catalysts were hydrothermally aged to simulate significant field use. Dual SCR dosing with newly developed controls played a critical role in achieving the proper split between the upstream LO-SCR and the downstream main SCR. Adding a next generation mixer for the downstream SCR proved essential in obtaining the final results. The optimal configuration required adding an electric heater to elevate the exhaust temperature at the LO-SCR for early cycle NOx reduction. The final results showed a 94.8% NOx reduction and 15.7% fuel savings on the composite NRTC.