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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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NASA NTRS2022

Lunar Communications Services with Emphasis on Commercialization

In mid-2020 Lockheed Marin Space (LM) and NASA’s Jet Propulsion Laboratory (JPL) formed a working group to study and address the need for a lunar communications network to service a growing lunar economy, beginning with the initial crewed and robotic mission needs in 2024. Multiple commercial relay architectures were studied and evaluated for platform requirements, communications capabilities, and commercial business viability in a growing ecosystem. The evolution of communications needs around the Moon were mapped to infrastructure build out. Trade studies were performed to evaluate reliability and lifetime requirements, and the viability of various data protocols. Mission concepts and operations plans were developed for both initial mission support and future autonomous network support. This work has led to Lockheed Martin and JPL to evaluate a single dedicated relay satellite in a frozen lunar orbit, with simultaneous coverage of the far-side and south pole landing sites for over 10 hours per day as a first step towards a comprehensive solution to lunar connectivity. This first satellite is compatible with an ESPA Grande launch volume and would be capable of launching on a rideshare into a variety of orbits and trajectories. The satellite is equipped with both high- and low-rate communications relay payloads with software-defined radios and a delay/disruption tolerant networking protocol. The system is designed to service initial and future mission needs in a commercialized manner, enabling a new class of missions to the Moon. The relay satellite leverages prior spacecraft platform work with on-orbit heritage in a lunar environment expected by 2023.

Davarian, Faramaz↗

DOE OSTI2021

Transfer-Learnt Energy Models for Predicting Electricity Consumption in Buildings with Limited and Sparse Field Data

Modeling energy consumption is critical for energy-efficient utilization of the electric appliances in a building, smart grid programs (like demand-response), and many other smart home applications. State-of-the-art energy modeling techniques either rely on theoretical models, or extensive instrumentation of the building envelope to gather ``big" data to train a deep neural network. While theoretical models are often limited by their estimation accuracy, it is not always feasible to gather a significant amount of field data. In this paper, we explore transfer learning-based strategies to train much more accurate model for energy estimation when using a sparse field data. We transferred knowledge, in the form of data and parameters, from the simulation framework to the field data. We evaluated the efficacy of our approach on field data collected from six commercial buildings and our results indicate that transfer learning-based models trained over one month data can perform comparative (and in some cases better) than the state-of-the-art machine learning and deep learning solutions.

Jain, Milan↗

NASA NTRS2011

Orion Flight Test-1 Thermal Protection System Instrumentation

The Orion Crew Exploration Vehicle (CEV) was originally under development to provide crew transport to the International Space Station after the retirement of the Space Shuttle, and to provide a means for the eventual return of astronauts to the Moon. With the current changes in the future direction of the United States human exploration programs, the focus of the Orion project has shifted to the project s first orbital flight test, designated Orion Flight Test 1 (OFT-1). The OFT-1 is currently planned for launch in July 2013 and will demonstrate the Orion vehicle s capability for performing missions in low Earth orbit (LEO), as well as extensibility beyond LEO for select, critical areas. Among the key flight test objectives are those related to validation of the re-entry aerodynamic and aerothermal environments, and the performance of the thermal protection system (TPS) when exposed to these environments. A specific flight test trajectory has been selected to provide a high energy entry beyond that which would be experienced during a typical low Earth orbit return, given the constraints imposed by the possible launch vehicles. This trajectory resulted from a trade study that considered the relative benefit of conflicting objectives from multiple subsystems, and sought to provide the maximum integrated benefit to the re-entry state-of-the-art. In particular, the trajectory was designed to provide: a significant, measureable radiative heat flux to the windward surface; data on boundary transition from laminar to turbulent flow; and data on catalytic heating overshoot on non-ablating TPS. In order to obtain the necessary flight test data during OFT-1, the vehicle will need to have an adequate quantity of instrumentation. A collection of instrumentation is being developed for integration in the OFT-1 TPS. In part, this instrumentation builds upon the work performed for the Mars Science Laboratory Entry, Descent and Landing Instrument (MEDLI) suite to instrument the OFT-1 ablative heat shield. The MEDLI integrated sensor plugs and pressure sensors will be adapted for compatibility with the Orion TPS design. The sensor plugs will provide in-depth temperature data to support aerothermal and TPS model correlation, and the pressure sensors will provide a flush air data system for validation of the entry and descent aerodynamic environments. In addition, a radiometer design will be matured to measure the radiative component of the reentry heating at two locations on the heat shield. For the back shell, surface thermocouple and pressure port designs will be developed and applied which build upon the heritage of the Space Shuttle Program for instrumentation of reusable surface insulation (RSI) tiles. The quantity and location of the sensors has been determined to balance the needs of the reentry disciplines with the demands of the hardware development, manufacturing and integration. Measurements which provided low relative value and presented significant engineering development effort were, unfortunately, eliminated. The final TPS instrumentation has been optimized to target priority test objectives. The data obtained will serve to provide a better understanding of reentry environments for the Orion capsule design, reduce margins, and potentially reduce TPS mass or provide TPS extensibility for alternative missions.

Kowal, T. John↗

NASA NTRSDate not supplied

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

The Runtime for Airspace Concept Evaluation (RACE) is an open-source software architecture and framework to build configurable, highly concurrent and distributed message-based systems that offer scalable, low-latency performance on commodity hardware. RACE was used in commercial aviation applications to rapidly build systems that span several machines (including synchronized displays), interface existing hardware simulators and other live data feeds, and incorporate sophisticated visualization components such as NASA WorldWind. These RACE applications validated elements of the FAA’s System Wide Information Management (SWIM) Program, handling up to 1000 messages/sec from diverse sources (SFDPS, TFM-DATA, TAIS, ASDE-X, ITWS and local ADS) for 4,500 simultaneous flights tracked in the next-generation air transportation system’s digital backbone. We have since generalized RACE to support Open Data Integration (ODIN) applications outside aviation. Systems built with RACE/ODIN can be deployed in the field, on commodity hardware, and operate with limited or intermittent connectivity to the outside world. Our primary use case is a web-server with local/persistent data storage that runs within and only serves the stakeholder network (e.g. an incident command post). We are tailoring the RACE/ODIN system to support wildland fire management for the upcoming NASA Wildland Fire Safety Demonstration Series. RACE-ODIN is under consideration for application in the Scalable Traffic Management for Emergency Response Operations project, or STEReO, which aims to create a system that can be deployed during emergencies, to coordinate multiple elements of disaster response. Such data sources predominantly come from existing services on the internet (e.g. weather and satellite data, imported from so called "edge servers") but can also include dynamic (real-time) data from computer simulations and within the stakeholder network (such as aircraft and personnel tracking information). We will present the architecture and ODIN system demonstration incorporating local data from instrumented power-line towers, interpolated weather data and geospatial data from space-based platforms.

Joseph C Coughlan↗

NASA NTRSDate not supplied

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

Guillaume P Brat↗

DOE OSTI2024

Towards in-situ certification of additively manufactured parts: the vital roles of physics-based and data-driven models

Certifying additively manufactured (AM) parts in-situ at the completion of a build is an enticing prospect, as it can help reduce the high costs associated with post-build testing and evaluation. However, achieving this goal presents significant challenges that may keep it aspirational for the foreseeable future. Nonetheless, incremental progress can pave the way forward. A critical aspect of in-situ certification involves continuous quality checking due to the random nature of the AM process and the difficulties in detecting defects or anomalies once layers are built over. While real-time in-situ monitoring strategies assisted by machine learning (ML) play a pivotal role in auditing part quality, they must ideally be supported by real-time (or near real-time) adaptive process control enabled by ML-assisted decision-making. By analyzing in-situ monitoring data in real-time (or near real- time) to dynamically adjust manufacturing parameters, such intervention can ensure AM parts are built to meet stringent certification standards. This can be achieved virtually by using high-fidelity performance models for the physical testing and evaluation tasks. In this short editorial, we discuss the key contributions made by data-driven and physics-based models in providing intelligence to the monitoring and process control tasks underpinning in-situ certification and in the simulation of the build’s performance under test and service conditions. While our focus lies in metal AM, the concepts discussed here are also relevant to other AM processes.

: In-situ monitoring↗

DOE OSTI2023

RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data

In modern science, big data plays an increasingly important role. Many scientific applications, such as running simulations on supercomputers or conducting experiments on advanced instruments, produce huge amount of data at unprecedented speed. Analyzing and understanding such big data is the key for scientists to make scientific breakthroughs. However, data might become unavailable for scientists to access when outages or maintenance of the storage system occur, which severely hinders scientific discovery. To improve the data availability, data duplication and erasure coding (EC) are often used. But as the scientific data gets larger, using these two methods can cause considerable storage and network overhead.In this paper, we propose RAPIDS, a hybrid approach that combines the multigrid-based error-bounded lossy compression with erasure coding, to significantly reduce the storage and network overhead required for maintaining high data availability. Our experiments show that RAPIDS reduces the storage overhead by up to 7.5x and network overhead by up to 3x to achieve the same level of availability compared to the regular EC method. We improve RAPIDS by building two models to optimize the fault tolerance configurations and data gathering strategy. We demonstrate that RAPIDS significantly improves performance when running on many CPU cores in parallel or on GPUs.

Wan, Lipeng↗

DOE OSTI2023

Interpreting T-History Data on Supercooling and Phase Change Enthalpy of a Salt-Hydrogel Complex for Building Thermal Management

Phase change materials (PCMs) are promising materials for storing and discharging latent heat in buildings to regulate the thermal environment. Measurement of salt hydrate PCM thermal performance is often challenging because of supercooling and phase segregation. Though differential scanning calorimetry (DSC) has been widely used to measure thermal properties of various phase change materials, DSC uses milligrams of sample and is unrealistic for predicting large-scale materials performance. The T-history method [1], in contrast, handles higher volumes but the analysis typically requires a lumped capacitance assumption. Here, we report and analyze T-History data on a novel salt-hydrogel complex with high viscosity, that renders low Biot number sample preparation extremely challenging. We re-examine the standard T-history method and compared against DSC data in this complex material. We report details of an experimental setup, built with necessary additions to a controlled environmental chamber. We carefully examine the validity of the lumped capacitance assumption and suggest a modified analysis using a computational approach for reliable data. Experimental parameters such as ramp rate and temperature range of the environmental chamber are considered via computational modeling to understand the effect of ramp rate on supercooling [2]. Finally, we report thermal cycling experiments on the salt-hydrogel complex. Our modified approach to measuring supercooling and enthalpy of fusion at large scales is important in better understanding the performance of phase-change materials at scale for building thermal storage. References: [1] Marin, Jose M, Belen Zalba, Luisa F Cabeza, and Harald Mehling. “Determination of Enthalpy Temperature Curves of Phase Change Materials with the Temperature-History Method: Improvement to Temperature Dependent Properties.” Measurement Science and Technology 14, no. 2 (February 1, 2003): 184–89. https://doi.org/10.1088/0957-0233/14/2/305. [2] Safari, A., R. Saidur, F.A. Sulaiman, Yan Xu, and Joe Dong. “A Review on Supercooling of Phase Change Materials in Thermal Energy Storage Systems.” Renewable and Sustainable Energy Reviews 70 (April 2017): 905–19. https://doi.org/10.1016/j.rser.2016.11.272

thermodynamics↗

DOE OSTI2023

Building the I (Interoperability) of FAIR for performance reproducibility of large-scale composable workflows in RECUP

Abstract-Scientific computing communities increasingly run their experiments using complex data- and compute-intensive workflows that utilize distributed and heterogeneous architectures targeting numerical simulations and machine learning, often executed on the Department of Energy Leadership Computing Facilities (LCFs). We argue that a principled, systematic approach to implementing FAIR principles at scale, including fine-grained metadata extraction and organization, can help with the numerous challenges to performance reproducibility posed by such workflows. We extract workflow patterns, propose a set of tools to manage the entire life cycle of performance metadata, and aggregate them in an HPC-ready framework for reproducibility (RECUP). We describe the challenges in making these tools interoperable, preliminary work, and lessons learned from this experiment.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Conditional distribution estimation of building characteristics with diffusion models for urban energy modeling

Understanding current energy consumption behavior in communities is critical for informing future energy use decisions and enabling efficient energy management. Urban energy models, which are used to simulate these energy use patterns, require large datasets with detailed building characteristics for accurate outcomes. However, such detailed characteristics at the individual building level are often unknown and costly to acquire, or unavailable. Through this work, we propose using a generative modeling approach to generate realistic building attributes to fill in the data gaps and finally provide complete characteristics as inputs to energy models. Our model learns complex, building-level patterns from training on a large-scale residential building stock model containing 2.2 million buildings. We employ a tabular diffusion-based framework that is designed to handle heterogeneous (discrete and continuous) features in tabular building data, such as occupancy, floor area, heating, cooling, and other equipment details. We develop a capability for conditional diffusion, enabling the imputation of missing building characteristics conditioned on known attributes. We conduct a comprehensive validation of our conditional diffusion model, firstly by comparing the generated conditional distributions against the underlying data distribution, and secondly, by performing a case study for a Baltimore residential region, showing the practical utility of our approach. Our work is one of the first to demonstrate the potential of generative modeling to accelerate building energy modeling workflows.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Hybrid Data-Driven Physics-Based Model Framework Implementation: Towards a Secure Cyber-Physical Operation of the Smart Grid

False data injection cyber-attack detection models on smart grid operation have been much explored recently, considering analytical physics-based and data-driven solutions. Recently, a hybrid data-driven physics-based model framework for monitoring the smart grid is developed. However, the framework has not been implemented in real-time environment yet. In this paper, the framework of the hybrid model is developed within a real-time simulation environment. OPAL-RT real-time simulator is used to enable Hardware-in-the-Loop testing of the framework. IEEE 9-bus system is considered as a testing grid for gaining insight. The process of building the framework and the challenges faced during development are presented. The performance of the framework is investigated under various false data injection attacks.

false data injection attack, machine learning, sta↗

DOE OSTI2024

Implementation and validation of optimal start control strategy for air conditioners and heat pumps

Commercial buildings are responsible for approximately 20 % of the total energy consumption and greenhouse gas emissions in the United States. Over 85 % of these buildings lack building automation systems, and many are small (<50,000 square feet), underserved, and use rooftop units (RTUs) for heating, ventilation, and air-conditioning needs. Because these buildings lack proper energy management systems, several operational deficiencies lead to excess energy consumption. Studies have shown that managing the RTUs’ heating and cooling set points, schedules, setbacks, and optimal start can result in a 20 % to 25 % reduction in electricity consumption in small commercial buildings. These buildings typically use fixed schedules to start the RTUs 60 to 120 min before occupancy begins, which results in excess energy consumption. This paper presents research that demonstrates and evaluates the performance of four optimal start methods, which utilize data-based modeling as a key element in facilitating adaptive control in response to time-varying inputs while requiring minimal sensor inputs. The evaluation found energy savings in two commercial buildings equipped with RTUs by periodically alternating four different optimal start models during the cooling and heating season. The resulting energy savings are positive for all models and range from 2 to 5 kWh/day/unit. The units on the east side of the building showed higher savings, while interior units showed greater variability in savings due to the differences in capacities and room sizes. Savings were considerably greater during the heating season compared to the cooling season. The performance of all four models on Mondays was poor; models suggested a shorter optimal start time, which resulted in relatively larger errors. Finally, the future work will look at using a different model for the days after weekends and holidays.

42 ENGINEERING↗

NASA NTRS2009

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is generally performed within two arenas: (1) Production testing for certification and acceptance, and (2) Developmental testing for prototype or experimental purposes. The customer base consists of NASA programs, DOD programs, and commercial programs. Resources in place to perform on-site testing include both civil servants and contractor personnel, hardware and software including data acquisition and control, and 6 test stands with a total of 14 test positions/cells. For several business reasons there is the need to augment understanding of the test costs for all the various types of test campaigns. Historical propulsion test data was evaluated and analyzed in many different ways with the intent to find any correlation or statistics that could help produce more reliable and accurate cost estimates and projections. The analytical efforts included timeline trends, statistical curve fitting, average cost per test, cost per test second, test cost timeline, and test cost envelopes. Further, the analytical effort includes examining the test cost from the perspective of thrust level and test article characteristics. Some of the analytical approaches did not produce evidence strong enough for further analysis. Some other analytical approaches yield promising results and are candidates for further development and focused study. Information was organized for into its elements: a Project Profile, Test Cost Timeline, and Cost Envelope. The Project Profile is a snap shot of the project life cycle on a timeline fashion, which includes various statistical analyses. The Test Cost Timeline shows the cumulative average test cost, for each project, at each month where there was test activity. The Test Cost Envelope shows a range of cost for a given number of test(s). The supporting information upon which this study was performed came from diverse sources and thus it was necessary to build several intermediate databases in order to understand, validate, and manipulate data. These intermediate databases (validated historical account of schedule, test activity, and cost) by themselves are of great value and utility. For example, for the Project Profile, we were able to merged schedule, cost, and test activity. This kind of historical account conveys important information about sequence of events, lead time, and opportunities for improvement in future propulsion test projects. The Product Requirement Document (PRD) file is a collection of data extracted from each project PRD (technical characteristics, test requirements, and projection of cost, schedule, and test activity). This information could help expedite the development of future PRD (or equivalent document) on similar projects, and could also, when compared to the actual results, help improve projections around cost and schedule. Also, this file can be sorted by the parameter of interest to perform a visual review of potential common themes or trends. The process of searching, collecting, and validating propulsion test data encountered a lot of difficulties which then led to a set of recommendations for improvement in order to facilitate future data gathering and analysis.

Ramirez-Pagan, Carmen P.↗

DOE OSTI2025

The relative importance of building design parameters in reducing energy use and sensible heat release from buildings in light of forecasted future weather data and building coverage ratio

Buildings typically have a 60-to-75-year lifespan before they require significant maintenance or modifications. However, most builders evaluate the performance of their new buildings using whole-building energy simulation tools based on the current typical meteorological year (TMY) file or actual meteorological year. The energy use consumption and sensible heat release pattern observed from buildings could potentially change based on shifting global climates. Therefore, the recommended energy-efficiency design parameters might also change during these periods. In this study, we evaluate the role of different building design parameters, such as material reflectivity, HVAC COP, and insulation values, on building energy usage and sensible heat release from buildings with different building coverage ratios (BCR), based on the current and future weather file TMY (fTMY) for the middle of the century (2040–2060). The role of sensible heat release from buildings is not accounted for accurately while estimating building energy usage in most whole-building energy simulations. The study conducts a series of whole-building energy simulation analyses using EnergyPlus to evaluate the role of different design parameters based on TMY and fTMY weather conditions. The analysis is conducted for two hot desert climatic cities: Phoenix (USA) and Abu Dhabi (UAE). The results show that, for the base case in a future climate, the sensible heat release is reduced by an average of 30% due to the reduced delta T between the surface and ambient air. Further, the results show an increase in total energy consumption by 5% annually. The results also show that, for buildings with traditional coatings, shorter buildings release more heat than taller buildings. On the other hand, for buildings with reflective paints, shorter buildings release less heat than taller buildings. The findings from this study can be used by policymakers, utility companies, and builders to better understand the relative role of different building design parameters while constructing new and retrofitting existing buildings.

Alhazmi, Mansour [King Fahd University of Petroleu↗

NASA NTRS1996

Aerodynamic Characteristics of Two Waverider-Derived Hypersonic Cruise Configurations

An evaluation was made on the effects of integrating the required aircraft components with hypersonic high-lift configurations known as waveriders to create hypersonic cruise vehicles. Previous studies suggest that waveriders offer advantages in aerodynamic performance and propulsion/airframe integration (PAI) characteristics over conventional non-waverider hypersonic shapes. A wind-tunnel model was developed that integrates vehicle components, including canopies, engine components, and control surfaces, with two pure waverider shapes, both conical-flow-derived waveriders for a design Mach number of 4.0. Experimental data and limited computational fluid dynamics (CFD) solutions were obtained over a Mach number range of 1.6 to 4.63. The experimental data show the component build-up effects and the aerodynamic characteristics of the fully integrated configurations, including control surface effectiveness. The aerodynamic performance of the fully integrated configurations is not comparable to that of the pure waverider shapes, but is comparable to previously tested hypersonic models. Both configurations exhibit good lateral-directional stability characteristics.

Cockrell, Charles E., Jr.↗

DOE OSTI2023

Resonant anomaly detection with multiple reference datasets

An important class of techniques for resonant anomaly detection in high energy physics builds models that can distinguish between reference and target datasets, where only the latter has appreciable signal. Such techniques, including Classification Without Labels (CWoLa) and Simulation Assisted Likelihood-free Anomaly Detection (SALAD) rely on a single reference dataset. They cannot take advantage of commonly available multiple datasets and thus cannot fully exploit available information. In this work, we propose generalizations of CWoLa and SALAD for settings where multiple reference datasets are available, building on weak supervision techniques. We demonstrate improved performance in a number of settings with realistic and synthetic data. As an added benefit, our generalizations enable us to provide finite-sample guarantees, improving on existing asymptotic analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1980

Solar energy system performance evaluation: Seasonal report for Contemporary-Manchester, Manchester, New Hampshire

The operational and thermal performance of the solar energy system, Contemporary-Manchester, is described. The system was designed by Contemporary Systems Incorporated to provide space heating and domestic hot water preheating for a three story dwelling located on the New Hampshire Vocational Technical College campus, Manchester, New Hampshire. The net fossil energy savings for the period from March, 1979 to February, 1980 was 14.52 million Btu. However, the performance of the system must be degraded due to the fact that the building was unoccupied throughout the data assessment and analysis period. The unoccupied status prevented the normal adjustment of heating and ventilating controls for maintenance of comfort levels within the building. This lack of occupancy also prevented the typical family hot water usage, which would have allowed for more realistic evaluation of the hot water subsystem.

Source record↗

NASA NTRS1990

The CRAF mission and Earth-based comet observations

The Comet Rendezvous Asteroid Flyby (CRAF) mission is now being designed and planned to perform detailed studies of a typical short period comet as it moves around its orbit, building on the data gained from the Giotto, Vega, and Suisei fast flybys of Comet Halley in 1986. CRAF will be launched in Aug. 1995 and will match orbits with short period Comet Kopff in July 2000, 850 days before perihelion at a heliocentric distance of 5.05 AU. After a series of close, slow flybys, the spacecraft will be placed in orbit around the nucleus for a better than 1 m/line-pair imaging resolution on the nucleus surface. Earth based observations of the target comet, either by ground based facilities or Earth orbiting satellites, can provide essential data for CRAF mission planning, and are needed in support of the rendezvous mission. Estimates of the nucleus size, albedo, shape, rotation period, and rotation pole orientation are needed for preliminary mission planning, resource allocation, and sequence design.

Weissman, Paul R.↗