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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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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

In Situ Data Infrastructure for Scientific Unit Testing Platform

Testing is a significant software development process for the management of software systems and scientific code. However, as the complexity of scientific codes increases, extra checks are needed to monitor impacts to dependent models and to verify system constraints. The software complexity also impedes the efforts of module developers and software engineers to rapidly develop and extend their code. Recently, we have developed an automatic methodology and prototype platform to facilitate scientific verification of individual functions within complex scientific codes. With this system, the scientific module builders are able to track variables conveniently in one module or track variables’ changes among different modules. In this paper, we present a procedure for automatic unit testing generation. For the interest of a general audience of this conference, we are emphasizing the technical details of integrating the In Situ data infrastructure into our platform. At the end of this paper, we have included an implementation of unit testing for the ACME Land Model (ALM) to demonstrate the usefulness and correctness of the platform. We have also used single- and multipoint checks to demonstrate the efficient variable tracking capability of this platform.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Control systems and data management for high-power laser facilities

The next generation of high-power lasers enables repetition of experiments at orders of magnitude higher frequency than what was possible using the prior generation. Facilities requiring human intervention between laser repetitions need to adapt in order to keep pace with the new laser technology. A distributed networked control system can enable laboratory-wide automation and feedback control loops. These higher-repetition-rate experiments will create enormous quantities of data. A consistent approach to managing data can increase data accessibility, reduce repetitive data-software development and mitigate poorly organized metadata. An opportunity arises to share knowledge of improvements to control and data infrastructure currently being undertaken. We compare platforms and approaches to state-of-the-art control systems and data management at high-power laser facilities, and we illustrate these topics with case studies from our community

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Addressing Critical Knowledge Gaps on Wildland Fires with UAS Technology

To better predict and respond to extreme fire behavior, wind shear, and superheated gases, there is a need for enhanced tactical microclimate wind forecasting. Collecting real-time or near-real-time three-dimensional atmospheric data during wildland fire suppression is vital for both ground firefighters and aviation safety. The use of balloons for soundings is not allowed due to aircraft operations, so new technology must be used. To address this need, the NASA FireSense Project has invested in co-developing and transitioning advanced technologies for atmospheric data collection to operational platforms to support decisions for wildland fire management. One of these technology investments has been with Uninhabited Aerial Systems (UAS) for atmospheric soundings. In collaboration with MITRE Corporation, a technology demonstration of Uninhabited Aerial Systems (UAS) for atmospheric soundings was held in Missoula, MT. This demonstration featured a NASA-designed payload on a Freefly Alta-X UAS, consistent with USFS UAS operations, balloon-borne soundings for data validation, and microscale modeling efforts. Results of this effort will be presented including comparison of forecasted conditions to data collection values as well as the impact on forecasts given real-time mixing heights and dispersion levels.

Jennifer Fowler↗
DOE OSTI2025

A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

LLVM↗
NASA NTRS1973

Near real time water resources data for river basin management

The author has identified the following significant results. Twenty Data Collection Platforms (DCP) are being field installed on USGS water resources stations in the Delaware River Basin. DCP's have been successfully installed and are operating well on five stream gaging stations, three observation wells, and one water quality monitor in the basin. DCP's have been installed at nine additional water quality monitors, and work is progressing on interfacing the platforms to the monitors. ERTS-related water resources data from the platforms are being provided in near real time, by the Goddard Space Flight Center to the Pennsylvania district, Water Resources Division, U.S. Geological Survey. On a daily basis, the data are computer processed by the Survey and provided to the Delaware River Basin Commission. Each daily summary contains data that were relayed during 4 or 5 of the 15 orbits made by ERTS-1 during the previous day. Water resources parameters relays by the platforms include dissolved oxygen concentrations, temperature, pH, specific conductance, well level, and stream gage height, which is used to compute stream flow for the daily summary.

Paulson, R. W.↗
DOE OSTI2016

ADMS State of the Industry and Gap Analysis

An Advanced distribution management system (ADMS) is a platform for optimized distribution system operational management. This platform comprises of distribution management system (DMS) applications, supervisory control and data acquisition (SCADA), outage management system (OMS), and distributed energy resource management system (DERMS). One of the primary objectives of this work is to study and analyze several ADMS component and auxiliary systems. All the important component and auxiliary systems, SCADA, GISs, DMSs, AMRs/AMIs, OMSs, and DERMS, are discussed in this report. Their current generation technologies are analyzed, and their integration (or evolution) with an ADMS technology is discussed. An ADMS technology state of the art and gap analysis is also presented. There are two technical gaps observed. The integration challenge between the component operational systems is the single largest challenge for ADMS design and deployment. Another significant challenge noted is concerning essential ADMS applications, for instance, fault location, isolation, and service restoration (FLISR), volt-var optimization (VVO), etc. There are a relatively small number of ADMS application developers as ADMS software platform is not open source. There is another critical gap and while not being technical in nature (when compared the two above) is still important to consider. The data models currently residing in utility GIS systems are either incomplete or inaccurate or both. This data is essential for planning and operations because it is typically one of the primary sources from which power system model are created. To achieve the full potential of ADMS, the ability to execute acute Power Flow solution is an important pre-requisite. These critical gaps are hindering wider Utility adoption of an ADMS technology. The development of an open architecture platform can eliminate many of these barriers and also aid seamless integration of distribution Utility legacy systems with an ADMS.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Future Online Analysis Platform Workshop Report

Recent technology trends, such as the increasing focus on data management technologies and the emergence of sustainable on-demand computing and commercial cloud facilities provide initial steps and potential building blocks for creating such a compute facility. How do we fill the gap between what we have now and the capabilities we need to make the vision of an online data facility a reality? What research challenges need to be addressed – and can be addressed – in the coming 5-10 years? How should we adjust our vision if they are not solved? Is such a facility compatible with the existing and evolving exascale resources and/or how should they evolve to be compatible? How do “beyond Moore’s law” technologies enable advanced data analysis? Those are the challeges that the Future Platform workshop was organized to address. This report is organized as follows. Section 2 summarizes data challenges and patterns related to the exemplar use cases presented during the first half day of the workshop. Section 3 summarizes the requirements presented by those use cases as well as a synthesis of those requirements into a Future Platform definition achieved on the 3rd half day of the workshop (morning of the 2nd day). Section 4 includes area breakout reports from the areas on the 2nd half day of the workshop (afternoon of the 1st day). Finally Section 5 has a report on recommendation for building methodology and metrics. The report concludes in Section 6.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Enabling a Decentralized Smart Grid Using Autonomous Edge Control Devices

As a large number of distributed devices are connected to the modern smart grid, the traditional centralized connectivity models fail to provide economic value. These models have relied on sending data to the cloud for processing and receiving commands to exert control actions, resulting in an ‘on-demand system’ with high bandwidth, low latency and an overload of data on the cloud. For realizing a decentralized system, there is a strong need to embed intelligence at the ‘edge of the network’. These intelligent devices, capable of sensing, local data processing and exerting control actions, report only actionable information to the cloud, acting as an edge control node. The system can then function autonomously, without constant cloud inputs, tolerating longer delays in communication, making the overall system ultra-low cost. The Global Asset Monitoring, Management and Analytics (GAMMA) Platform is a novel ultralow- cost, secure platform that operates through a Bluetooth based delay tolerant network. It relies on so-called ‘data mules’ to bridge the last mile connectivity gap in an inherently secure way. Due to this model, the platform requires no in-country certifications, does not rely on a dedicated backhaul technology and is immune to technology migration. This architecture also addresses some gaps identified in traditional IoT-based solutions in remote areas and sparse connectivity. A functional unit of the edge computing node has been built, taking into account various constraints like costs, customizations, data storage, cybersecurity and power management. Here, the platform has been built, deployed and has demonstrated distributed smart grid applications like power quality sensing, automated metering infrastructure and utility asset monitoring.

42 ENGINEERING↗
DOE OSTI2019

Bi-Level Volt-VAR Optimization to Coordinate Smart Inverters with Voltage Control Devices

Conservation voltage reduction (CVR) uses voltage control to reduce customer power demand and help improve the operational efficiency of the electric power distribution system. With the advent of advanced distribution management systems (ADMS), the underlying data and control-rich platform can be utilized to enable a centralized Volt-VAR optimization (VVO) scheme that includes smart inverter controls along with legacy voltage control devices such as voltage regulators and capacitor banks to ensure a maximum CVR benefit. The objective of this paper to present a VVO approach that controls system’s legacy voltage control devices and coordinates their operation with smart inverter control. An optimal power flow (OPF) formulation is proposed by developing linear and nonlinear power flow approximations for a three-phase unbalanced electric power distribution system. A bi-level VVO approach is proposed where, Level-1 optimizes the control of legacy devices and smart inverters using a linear approximate three-phase power flow. In Level-2, the control parameters for smart inverters are adjusted to obtain an optimal and feasible solution by solving the approximate nonlinear OPF model. Level-1 is modeled as a Mixed Integer Linear Program (MILP) while Level-2 as a Quadratically Constrained Quadratic Program (QCQP). The proposed approach is validated using IEEE test cases and the results demonstrate the applicability of the framework in achieving the CVR objective.

Jha, Rahul Ranjan↗
DOE OSTI2014

Standard Energy Efficiency Data Platform

The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.

Cheifetz, D.Magnus↗
NASA NTRS1975

Operational considerations for the application of remotely sensed forest data from LANDSAT or other airborne platforms

Research in the application of remotely sensed data from LANDSAT or other airborne platforms to the efficient management of a large timber based forest industry was divided into three phases: (1) establishment of a photo/ground sample correlation, (2) investigation of techniques for multi-spectral digital analysis, and (3) development of a semi-automated multi-level sampling system. To properly verify results, three distinct test areas were selected: (1) Jacksonville Mill Region, Lower Coastal Plain, Flatwoods, (2) Pensacola Mill Region, Middle Coastal Plain, and (3) Mississippi Mill Region, Middle Coastal Plain. The following conclusions were reached: (1) the probability of establishing an information base suitable for management requirements through a photo/ground double sampling procedure, alleviating the ground sampling effort, is encouraging, (2) known classification techniques must be investigated to ascertain the level of precision possible in separating the many densities involved, and (3) the multi-level approach must be related to an information system that is executable and feasible.

Baker, G. R.↗
NASA NTRS1982

Development of data processing interpretation and analysis system for the remote sensing of trace atmospheric gas species

Problems associated with the development of the measurement of air pollution from satellites (MAPS) experiment program are addressed. The primary thrust of this research was the utilization of the MAPS experiment data in three application areas: low altitude aircraft flights (one to six km); mid altitude aircraft flights (eight to 12 km); and orbiting space platforms. Extensive research work in four major areas of data management was the framework for implementation of the MAPS experiment technique. These areas are: (1) data acquisition; (2) data processing, analysis and interpretation algorithms; (3) data display techniques; and (4) information production.

Casas, J. C.↗
NASA NTRS1983

Space Station needs, attributes and architectural options. Volume 2, book 2, part 1: Mission implementation concepts

The overall configuration and modules of the initial and evolved space station are described as well as tended industrial and polar platforms. The mass properties that are the basis for costing are summarized. User friendly attributes (interfaces, resources, and facilities) are identified for commercial; science and applications; industrial park; international participation; national security; and the external tank option. Configuration alternates studied to determine a baseline are examined. Commonality for clustered 3-man and 9-man stations are considered as well as the use of tethered platforms. Requirements are indicated for electrical, communication and tracking; data management Subsystem requirements for electrical, data management, communication and tracking, environment control/life support system; and guidance navigation and control subsystems are identified.

Source record↗
DOE OSTI2014

Standard Energy Efficiency Data Platform

The SEED platform is expected to be a building energy performance data management tool that provides federal, state and local governments, building owners and operators with an easy, flexible and cost-effective method to collect information about groups of buildings, oversee compliance with energy disclosure laws and demonstrate the economic and environmental benefits of energy efficiency. It will allow users to leverage a local application to manage data disclosure and large data sets without the IT investment of developing custom applications. The first users of SEED will be agencies that need to collect, store, and report/share large data sets generated by benchmarking, energy auditing, retro-commissioning or retrofitting of many buildings. Similarly, building owners and operators will use SEED to manage their own energy data in a common format and centralized location. SEED users will also control the disclosure of their information for compliance requirements, recognition programs such as ENERGY STAR, or data sharing with the Buildings Performance Database and/or other third parties at their discretion.

Cheifetz, D. Magnus↗
DOE OSTI2022

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2021. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data.

energy efficiency mobility↗
DOE OSTI2023

Livewire Data Platform-A Solution for Energy Efficient Mobility Systems (EEMS) Data Sharing

This presentation is an overview of progress made on the Livewire Data Platform since June 2022. Livewire is a publicly accessible platform for sharing energy efficiency and mobility research data funded by DOE's Vehicle Technologies Office. Core services and platform capabilities of Livewire include: Free, secure data storage; Access management that allows data owners to control who sees their data; Data collection and preservation; Quality characterization; Detailed access and download metrics; and Increased visibility of projects and data. Anyone can create an account and access data at https://livewire.energy.gov/.

energy efficiency↗
NASA NTRS2017

Applications of Satellite Data to Support Improvements in Irrigation and Groundwater Management in California

In agricultural regions around the world, threats to water supplies from drought and groundwater depletion are driving increased demand for tools to advance agricultural water use efficiency and support sustainable groundwater management. Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water resource managers with information that can be used to both optimize ag water use and improve estimates of groundwater withdrawals for irrigation. We describe the development of two remote sensing-based tools for ET mapping in California, including important lessons in terms of system design, partnership development, and transition to operations. For irrigation management, the integration of satellite data and surface sensor networks to provide timely delivery of information on crop water requirements can make irrigation scheduling more practical, convenient, and accurate.Developed through a partnership between NASA and the CA Department of Water Resources, the Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development and crop water requirements at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based interface and web data services. SIMS also provides an API that facilitates integration with other irrigation decision support tools, such as CropManage and IrriQuest. Field trials using these integrated tools have shown that they can be used to sustain yields while improving water use efficiency and nutrient management. For sustainable groundwater management, the combination of satellite-derived estimates of ET and data on surface water deliveries for irrigation can increase the accuracy of estimates of groundwater pumping. We are developing an OpenET platform to facilitate access to ET data from multiple models and accelerate operational use of ET data in support of a range of water management applications, including implementation of the Sustainable Groundwater Management Act in CA. By providing a shared basis for decision making, we anticipate that the OpenET platform will accelerate implementation of solutions for sustainable groundwater management.

Satellite↗