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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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The Building Stock Visualization Platform uses web-based technologies to display information on the input assumptions and output results of building stock modeling tools for building energy audits.
Phil Engelauf, STS-114 Mission Operations Representative reports: the orbital rendezvous was successful, and today's activities includes initial preparations of the next day's extravehicular activities (EVA); he specifically mentioned tile repair, wiring on the outside of the vehicle to try to recover CMG2 (Control Moment Gyro), and preparation for the external stowage platform. John Shannon, Manager of the Space Shuttle Operations and Integration reports from Engineering standpoint that the composites of the underside of the tile surface seen from pictures taken during the pitch maneuver were extremely clean; the Engineering staff continues to look at the focus inspection data from the orbital boom sensor system (OBSS) and other data to assess the condition of the vehicle. Solid rocket boosters were retrieved and are towed back to the Air Force hangar in Cape Carneval. Six target inspection (nose gear doors, gap fillers, chine area, external tank doors, trailing edge, and ice), and arm operations, foam, conservation measures, shuttle air lock, aerodynamics assessment and re-entry were topics covered with the News media.
As interest in space exploration grows, developing a lunar habitat has become a key component of extending missions into deep space. To guarantee reliable power management of a habitat’s DC microgrid, control schemes are needed that can manage the different assets (batteries, photovoltaics, loads) effectively. Proposed hierarchical control schemes are further developed into hardware solutions using Opal-RT’s real-time simulation software and Power Hardware-in-the-Loop platform. Experimental results of a simulated DC microgrid and physical DC/DC components can allow better realization and performance of applications such as battery discharge control.
The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center's (GSFC) Scientific and Educational Endeavors (SEE) and the Center for Image Processing in Education (CIPE) use satellite image processing as part of their science lessons developed for students and educators. The image processing products that they use, as part of these lessons, no longer fulfill the needs of SEE and CIPE because these products are either dependent on a particular computing platform, hard to customize and extend, or do not have enough functionality. SEE and CIPE began looking for what they considered the "perfect" image processing tool that was platform independent, rich in functionality and could easily be extended and customized for their purposes. At the request of SEE, NASA's GSFC, code 588 the Advanced Architectures and Automation Branch developed a powerful new Java based image processing endeavors.
This paper describes Web-Altairis, an Internet-enabled ground system software package funded by the Advanced Automation and Architectures Branch (Code 588) of NASA's Goddard Space Flight Center. Web-Altairis supports the trend towards "lights out" ground systems, where the control center is unattended and problems are resolved by remote operators. This client/server software runs on most popular platforms and provides for remote data visualization using the rich functionality of the VisAGE toolkit. Web-Altairis also supports satellite commanding over the Internet. This paper describes the structure of Web-Altairis and VisAGE, the underlying technologies, the provisions for security, and our experiences in developing and testing the software.
The Community Coordinated Modeling Center (CCMC) at NASA Goddard Space Flight Center (GSFC) leads heliophysics research by providing open access to numerous models and their outputs. Our resources are available on-demand and continuously updated with real-time data, covering sun-earth interactions across multiple domains. These domains include coronal, heliosphere, inner and global magnetosphere, ionosphere, thermosphere, and lower atmosphere interactions. Operating in a hybrid environment, CCMC utilizes both self-owned hardware and Amazon Web Services (AWS) cloud infrastructure. Managing petabytes of data across multiple locations necessitates robust data engineering solutions. To address this challenge, CCMC has adopted industry-standard and open-source tools. We use Apache Airflow as our primary data engineering platform, Python for scripting and data processing, and GitLab for version control and CI/CD. Additionally, we employ Kubernetes for containerized services, Grafana and Prometheus for metrics and monitoring, and Terraform and Puppet for reproducible infrastructure as code. This presentation will discuss lessons learned from our data engineering experiences, platforms evaluated but found unsuitable for our scientific data requirements, and specific techniques developed to enhance data transfer speed and reliability. By using these technologies effectively, CCMC continues to advance heliophysics research through efficient data management and open-access modeling.
This article presents the design, implementation, and use cases of the Chattanooga Digital Twin (CTwin) towards the vision for next-generation smart city applications for urban mobility management. CTwin is an end-to-end web-based platform that incorporates various aspects of the decision-making process for optimizing urban transportation systems in Chattanooga, Tennessee, to reduce traffic congestion, incidents, and vehicle fuel consumption. The platform serves as a cyberinfrastructure to collect and integrate multi-domain urban mobility data from various online repositories and Internet of Things (IoT) sensors, covering multiple urban aspects (e.g., traffic, natural hazards, weather, and safety) that are relevant to urban mobility management. The platform enables advanced capabilities for: (a) real-time situational awareness on traffic and infrastructure conditions on highways and urban roads, (b) cyber-physical control for optimizing traffic signal timing, and (c) interactive visual analytics on big urban mobility data and various metrics for traffic prediction and transportation performance evaluation. The platform is designed using a multi-level componentization paradigm and is implemented using modular and adaptive architecture, rendering it as a generalizable and extendable prototype for other urban management applications. We present several use cases to demonstrate CTwin's core capabilities for supporting decision-making in smart urban mobility management.
Field Programmable Gate Arrays (FPGA) have played increasingly important roles in military and aerospace applications. Xilinx SRAM-based FPGAs have been extensively used in commercial applications. They have been used less frequently in space flight applications due to their susceptibility to single-event upsets. Reliability of these devices in space applications is a concern that has not been addressed. The objective of this project is to design a fully programmable hardware/software platform that allows (but is not limited to) comprehensive static/dynamic burn-in test of Virtex-II 3000 FPGAs, at speed test and SEU test. Conventional methods test very few discrete AC parameters (primarily switching) of a given integrated circuit. This approach will test any possible configuration of the FPGA and any associated performance parameters. It allows complete or partial re-programming of the FPGA and verification of the program by using read back followed by dynamic test. Designers have full control over which functional elements of the FPGA to stress. They can completely simulate all possible types of configurations/functions. Another benefit of this platform is that it allows collecting information on elevation of the junction temperature as a function of gate utilization, operating frequency and functionality. A software tool has been implemented to demonstrate the various features of the system. The software consists of three major parts: the parallel interface driver, main system procedure and a graphical user interface (GUI).
Pursuing controlled fusion is a monumental endeavor that promises to unlock a transformational source of clean energy. Here, the International Sherwood Fusion Theory Conference is a crucial platform for researchers to discuss the physics governing plasmas in fusion-relevant configurations. From exploring the fundamental properties of plasma to cutting-edge computer simulation techniques, this conference fosters innovation and collaboration, propelling us closer to realizing the dream of a fusion-powered future.
NASA’s Geospace Dynamics Constellation (GDC) mission will study the effect of space weather phenomena on Earth’s upper atmosphere ion and neutral gases and, in turn, their impact on human assets. GDC will provide multi-point observations to determine how the Earth’s upper atmosphere is driven to dynamic changes and extremes by the solar wind. Magnetospheric energy input, both kinetic and electromagnetic, will be captured by the Comprehensive Auroral Precipitation Experiment (CAPE), the Thermal Plasma Sensor (TPS), and the Near Earth Magnetometer Instrument in a Small Integrated System (NEMISIS). CAPE captures the complete kinetic energy inputs with observations of the precipitating and upgoing electrons and precipitating ions. TPS captures part of the electromagnetic energy inputs with observations of the thermal plasma velocity that map E-field inputs, and NEMISIS captures the other part of the electromagnetic energy input with measurements of magnetic field variations due to field aligned currents. We use similar observations from the Defense Meteorological Space Platform (DMSP) satellites to demonstrate the balance between the different energy inputs (electron and ion Joule heating and Poynting flux) during the different phases of storms. We explore the local time and spatial structure and the impact they have on atmospheric density and winds with simulations of the Global Ionosphere and Thermosphere Model (GITM) and demonstrate how GDC will enable us to reconstruct those energy inputs locally and regionally
This paper presents performance evaluation of hierarchical optimization and control for distributed energy resource management system (DERMS) in large distribution networks via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory environment, including the accurate modeling of a full-scale distribution system of 11,000 nodes, the DERMS software controller, and 90 power hardware photovoltaics (PVs) and battery inverters. The applied DERMS algorithm is designed based on a realtime optimal power flow algorithm and implemented with acceleration design that performs fast dispatch of simulated PVs and real physical hardware DER devices every 4 seconds.
Long-range electronic ordering descending from a metallic parent state constitutes a rich playground to study the interplay of structural and electronic degrees of freedom. In this framework, kagome metals are in the most interesting regime where both phonon and electronically mediated couplings are significant. Several of these systems undergo a charge density wave transition. However, to date, the origin and the main driving force behind this charge order is elusive. Here, we use the kagome metal ScV 6 Sn 6 as a platform to investigate this problem, since it features both a kagome-derived nested Fermi surface and van-Hove singularities near the Fermi level, and a charge-ordered phase that strongly affects its physical properties. By combining time-resolved reflectivity, first principles calculations and photo-emission experiments, we identify the structural degrees of freedom to play a fundamental role in the stabilization of charge order, indicating that ScV 6 Sn 6 features an instance of charge order predominantly originating from phonons.
This paper presents performance evaluation of hierarchical optimization and control for distributed energy resource management system (DERMS) in large distribution networks via an advanced hardware-in-the-loop (HIL) platform. The HIL platform provides realistic testing in a laboratory envi-ronment, including the accurate modeling of a full-scale dis-tribution system of 11,000 nodes, the DERMS software con-troller, and 90 power hardware photovoltaics (PVs) and bat-tery inverters. The applied DERMS algorithm is designed based on a real-time optimal power flow algorithm and im-plemented with acceleration design that performs fast dis-patch of simulated PVs and real physical hardware DER devices every 4 seconds.
Increasingly, scientific research discoverydepends on the analysis of extremely large amounts of data. Thisdata is gathered through very large scientific instruments, verylarge numbers of small devices, and mid-scale instruments.These devices generate exponentially increasing volumes of data.Such data is often obtained, analyzed, stored, visualized, andtransferred at and among sites world-wide by largecollaborations of science communities. Managing and movingextremely large volumes of data across today’s networks is aspecial multidimensional challenge. Also, existing datamanagement and movement services and tools often areinadequate to address all specific requirements. This paperdescribes the various components of this challenge and howthose issues can be addressed by ROBIN, a uniquecomprehensive set of integrated services designed specificallyfor managing and moving extremely large amounts of data overlong distances, e.g., thousands of miles around the globe. Thispaper also describes the results of initial experiments using thatset of integrated services.
NASA is designing the Ares V heavy-lift cargo launch vehicle to send more crew and cargo to more places on the lunar surface than the 1960s-era Saturn V and to provide ongoing support for a permanent lunar outpost. This uncrewed cargo vehicle is designed to operate together with the Ares I crew vehicle (Figure 1). In addition to this role, however, its unmatched mass and volume capability represent a national asset for exploration, science, and commerce. The Ares V also enables or significantly enhances a large class of space missions not thought possible by scientists and engineers since the Saturn V program ended over 30 years ago. Compared to current systems, it will offer approximately five times the mass and volume to most orbits and locations. This should allow prospective mission planners to build robust payloads with margins that are three to five times the industry norm. The space inside the planned payload shroud has enough usable volume to launch the volumetric equivalent of approximately 10 Apollo Lunar Modules or approximately five equivalent Hubble Space Telescopes. This mass and volume capability to low-Earth orbit (LEO) enables a host of new scientific and observation platforms, such as telescopes, satellites, planetary and solar missions, as well as being able to provide the lift for future large in-space infrastructure missions, such as space based solar power and mining, Earth asteroid defense, propellant depots, etc. In addition, payload designers may also have the option of simplifying their designs or employing Ares V s payload as dumb mass to reduce technical and operational risk. The Ares V team is engaging the potential payload community now, two to three years before System Requirements Review (SRR), in order to better understand the additional requirements from the payload community that could be accommodated in the Ares V design in its conceptual phase. This paper will discuss the Ares V reference mission and capability, as well as its potential to perform other missions in the future.
The rapid growth of distributed energy resources (DERs) has prompted increasing interest in the monitoring and control of DERs through hybrid smart grid communications. The deployment of communications and computation has transformed the traditional physical power grid into a smart cyber-physical system (CPS). To fully understand the interdependency between physical grid and cyber netowrks, this study designed a power and communications hardware-in-the-loop (PCommHIL) CPS architecture, which enables the flexible verification of DER monitoring and control with hybrid communications architectures and Internet protocols. Design, development and case study of a PCommHIL testbed for the DER coordination are discussed in detail, and the proposed platform integrates DER devices, Advanced Metering Infrastructures (AMIs), and a suite of hybrid communications networks for distribution automation applications. Case study on DER situational awareness and Volt-Var control validates the efficacy of this proposed PCommHIL platform with hybrid communications designs. Results show that the HAN communication technologies play a critical role in hybrid designs and it is the bottleneck for DER applications. High performance communication technologies are highly recommended to be applied in the HAN for enhanced monitoring and real-time control of DERs.
Allosteric transcription factors (aTF) regulate gene expression through conformational changes induced by small molecule binding. Although widely used as biosensors, aTFs have proven challenging to design for detecting new molecules because mutation of ligand-binding residues often disrupts allostery. Here, we develop Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screen a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures – four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone – as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identifies biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design shows shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we develop cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid and scalable design of new biosensors, overcoming constraints of natural biosensors.
The assessment and forecasting of air quality around the world at high spatial and temporal resolution can be enhanced by integrating data from multiple sources including models, satellites, regulatory monitors, and low-cost sensors. Such integration is subject to numerous technical challenges, however, including heterogeneous data resolution and formatting, different levels of data availability and reliability, and computational and capacity challenges to developing data fusion tools and platforms. This presentation will provide an overview of a NASA-funded effort to develop a data fusion system within the Google Earth Engine platform which integrates these air quality data sources to produce comprehensive assessments and forecasts of key air pollutants at sub-daily and sub-city scales. The system is being developed in collaboration with city- and regional-level air quality managers, and will provide them with information to the assess and anticipate the health impacts of poor air quality, track local changes in air quality due to ongoing transportation and land use changes, and identify potential gaps in their current air quality monitoring strategies. The presentation will report advances achieved through the project, including bringing local air quality monitoring data into Google Earth Engine, quantifying uncertainties in air quality estimates and forecasts, and tailored communications tools providing integration into end-user processes to meet their needs.