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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing Power Resilience for Remote Communities: A Comprehensive Renewable Energy Solution for Itbayat Island

The island of Itbayat, Philippines, faces significant challenges in maintaining a reliable and resilient power supply due to its current reliance on a vulnerable power distribution system managed by a local electric cooperative. The existing infrastructure, which includes diesel generators and a radial network configuration with some above-ground lines, is highly susceptible to frequent typhoons and adverse weather conditions. These factors, combined with inadequate staffing and high operational costs, result in frequent power outages that disrupt daily life and hinder economic development. This white paper proposes a comprehensive solution to enhance the resilience and reliability of Itbayat's power system by integrating renewable energy sources, specifically solar photovoltaic (PV) systems, battery storage, and a microgrid controller. The proposed solution aims to reduce dependency on diesel fuel, optimize energy use, and provide a sustainable and robust power supply for the island. Key components of the solution include: 1. Solar PV Installation: Deploying solar PV panels to harness abundant solar energy, reducing reliance on diesel fuel. 2. Battery Storage Systems: Installing battery storage to store excess solar energy and ensure a continuous power supply during low solar generation periods. 3. Microgrid Controller: Implementing a microgrid controller to manage and optimize the integration of solar PV, battery storage, and existing diesel generators. The proposed solution addresses several critical issues, including system vulnerability, generator dependency, and operational inefficiencies. By adopting this innovative approach, Itbayat Island can achieve a more resilient, efficient, and sustainable energy infrastructure, ensuring a stable power supply for its residents and enhancing overall energy security.

14 SOLAR ENERGY↗
DOE OSTI2023

IceNet for FireBox - A Berkeley Warehouse-Scale Computer

Berkeley’s FireBox is a next-generation warehouse-scale computer (WSC) that utilizes the energy-efficiency and bandwidth density of integrated silicon-photonic interconnects to enable a new high-bandwidth and low-latency network fabric connecting thousands of compute nodes to petabytes of DRAM and Flash storage. The high bandwidth, low latency and high connectivity of FireBox’s WSC network fabric (IceNet) will enable dramatic improvements in the overall system energy efficiency enabling fine-grain power control on system resources (processors, links and memory/storage components). IceNet is a special 3-stage photonic Clos network architected to achieve ultra-low-latency connectivity between processor nodes and memory, drastically cutting down on the energy wasted in resource idling (processors and memory stalled due to pending network requests). This is achieved by integration of the first and last switch stages into processor/memory hub clients and by heavy over-provisioning of the high-radix middle switches (FlareSwitches). A key hardware component developed in this program is an active laser power management photonic integrated circuits called LightSpark. It interacts with the FlareSwitch and provides laser power to a subset of occupied switch ports, increasing the utilization of laser light in the photonic network by an order of magnitude. In addition to guiding the laser power where it is needed, the laser-power management module enables both wavelength and laser redundancy, significantly increasing the robustness of the system. The goal of the IceNet fabric is to enable communication between 1000s of processor nodes and PBs of memory/storage with <100ns latency, <10pJ/b wall-plug energy cost at multiple Pb/s of available connectivity bandwidth. These metrics represent two-orders of magnitude improvement with respect to the status of current data-center technology.

42 ENGINEERING↗
NASA NTRS2012

A Brief Review of the Need for Robust Smart Wireless Sensor Systems for Future Propulsion Systems, Distributed Engine Controls, and Propulsion Health Management

Smart Sensor Systems with wireless capability operational in high temperature, harsh environments are a significant component in enabling future propulsion systems to meet a range of increasingly demanding requirements. These propulsion systems must incorporate technology that will monitor engine component conditions, analyze the incoming data, and modify operating parameters to optimize propulsion system operations. This paper discusses the motivation towards the development of high temperature, smart wireless sensor systems that include sensors, electronics, wireless communication, and power. The challenges associated with the use of traditional wired sensor systems will be reviewed and potential advantages of Smart Sensor Systems will be discussed. A brief review of potential applications for wireless smart sensor networks and their potential impact on propulsion system operation, with emphasis on Distributed Engine Control and Propulsion Health Management, will be given. A specific example related to the development of high temperature Smart Sensor Systems based on silicon carbide electronics will be discussed. It is concluded that the development of a range of robust smart wireless sensor systems are a foundation for future development of intelligent propulsion systems with enhanced capabilities.

Hunter, Gary W.↗
NASA NTRS1973

Evolution of the satellite telemetry data processing facility at the Goddard Space Flight Center.

Data from scientific and application satellites managed by the NASA Goddard Space Flight Center are acquired through the world-wide Spacecraft Tracking and Data Network (STDN). These data are forwarded to a central telemetry data processing facility whose primary objective is the timely provision of the data to users in a form suitable for their analysis. In a successful evolution, a satellite data processing facility must adapt to changing support requirements while operationally supporting active spacecraft. Advances in the technology of data transmission, data storage systems, and file management make it feasible to implement a third-generation system which will be able to satisfy experimenter requirements for the next ten years.

Keipert, F. A.↗
DOE OSTI2022

Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

This article is about the state of ICON principles Goldman et al. (2021), https://doi.org/10.1029/2021EO153180 in natural hazards and a discussion on the opportunities and challenges of adopting them. Natural hazards pose risks to society, infrastructure, and the environment. Hazard interactions and their cascading phenomena in space and time can further intensify the impacts. Natural hazards’ risks are expected to increase in the future due to environmental, demographic, and socioeconomic changes. It is important to quantify and effectively communicate risks to inform the design and implementation of risk mitigation and adaptation strategies. Multihazard multisector risk management poses several nontrivial challenges, including: (a) integrated risk assessment, (b) Earth system data-model fusion, (c) uncertainty quantification and communication, and (d) crossing traditional disciplinary boundaries. Here, we review these challenges, highlight current research and operational endeavors, and underscore diverse research opportunities. We emphasize the need for integrated approaches, coordinated processes, open science, and networked efforts (ICON) for multihazard multisector risk management.

58 GEOSCIENCES↗
NASA NTRS2006

X-Windows Socket Widget Class

The X-Windows Socket Widget Class ("Class" is used here in the object-oriented-programming sense of the word) was devised to simplify the task of implementing network connections for graphical-user-interface (GUI) computer programs. UNIX Transmission Control Protocol/Internet Protocol (TCP/IP) socket programming libraries require many method calls to configure, operate, and destroy sockets. Most X Windows GUI programs use widget sets or toolkits to facilitate management of complex objects. The widget standards facilitate construction of toolkits and application programs. The X-Windows Socket Widget Class encapsulates UNIX TCP/IP socket-management tasks within the framework of an X Windows widget. Using the widget framework, X Windows GUI programs can treat one or more network socket instances in the same manner as that of other graphical widgets, making it easier to program sockets. Wrapping ISP socket programming libraries inside a widget framework enables a programmer to treat a network interface as though it were a GUI.

Barry, Matthew R.↗
DOE OSTI2020

Optimal carbon storage reservoir management through deep reinforcement learning

Model-based optimization plays a central role in energy system design and management. The complexity and high-dimensionality of many process-level models, especially those used for geosystem energy exploration and utilization, often lead to formidable computational costs when the dimension of decision space is also large. This work adopts elements of recently advanced deep learning techniques to solve a sequential decision-making problem in applied geosystem management. Specifically, a deep reinforcement learning framework was formed for optimal multiperiod planning, in which a deep Q-learning network (DQN) agent was trained to maximize rewards by learning from high-dimensional inputs and from exploitation of its past experiences. To expedite computation, deep multitask learning was used to approximate high-dimensional, multistate transition functions. Both DQN and deep multitask learning are pattern based. As a demonstration, the framework was applied to optimal carbon sequestration reservoir planning using two different types of management strategies: monitoring only and brine extraction. Both strategies are designed to mitigate potential risks due to pressure buildup. Results show that the DQN agent can identify the optimal policies to maximize the reward for given risk and cost constraints. Finally, experiments also show that knowledge the agent gained from interacting with one environment is largely preserved when deploying the same agent in other similar environments.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Connected Traffic Signal Coordination Optimization Framework through Network-Wide Adaptive Linear Quadratic Regulator–Based Control Strategy

Traffic congestion in metropolitan areas causes several significant challenges, such as longer travel times, decreased productivity, increased fuel consumption and vehicle emissions, and even severe injuries during crashes. Traffic signal control is a management approach to reduce traffic congestion and allocate the appropriate right of way for safety and mobility efficiency, both in temporal and spatial domains. Here, this study proposes a network-wide adaptive signal control coordination optimization framework based on the linear quadratic regulator algorithm. The traffic flow conditions driven by signal control inputs are formulated based on their network-wide state-space representation. After modeling traffic control regulation constraints, an adaptive linear quadratic regulator algorithm is designed to maximize the network-wide total throughput under the current conditions. Optimal signal control split time durations for multiple intersections in the network are derived by solving the algebraic Riccati equation. Furthermore, the recursive least square parameter estimation method is employed to quantify dynamic traffic condition changes. To verify the effectiveness of this proposed signal control framework, both simulation and real-world experimental tests are conducted for multiple intersections in downtown Chattanooga, Tennessee, United States. In preparation for real-world experimental tests, pipelines for real-time data processing implementation and historical traffic flow data analysis are conducted. The test results demonstrate that the proposed control framework achieves a decrease in travel time by up to 19.4%, total time spent (TTS) by up to 11.9%, and relative queue balance (RQB) by up to 15.6%. The research findings indicate that the proposed signal control framework can be generalized to handle large scale signal control optimization network-wide.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2024

Communications System Concept of Operations (ConOp) for Supporting Second Shift (SS) Operations

Wildland fires take place most often in remote areas without access to communications infrastructure. Communication during wildfire operations is crucial for safe and effective command and control of air assets, ground-based firefighters, and fire management. Without connectivity, Incident Command (IC) cannot exchange information, receive alerts or work with all parties involved in the wildfire suppression operation. Current policy directs IC to use voice radio communications, which require no prior infrastructure, to provide information needed for the command, control and safety of personnel and resources. Cellular communications are used only for logistical purposes unless no other method is available. To address some of the shortcomings of the current state of communications, the Advanced Capabilities for Emergency Response Operations (ACERO) Second Shift (SS) technical team is developing characteristics of an air-to-ground Mesh Radio System (MRS) and preparing for a future demonstration. The MRS will allow air and ground assets to automatically join a radio network without relying on existing infrastructure and exchange information critical to maintaining situation awareness and air traffic management by the onsite IC. The MRS will also give users more options for communications in addition to voice communications.

David Fuller↗
NASA NTRSDate not supplied

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗
NASA NTRS2003

Preserving the Finger Lakes for the Future: A Prototype Decision Support System for Water Resource Management, Open Space, and Agricultural Protection

As described herein, this project has progressed well, with the initiation or completion of a number of program facets at programmatic, technical, and inter-agency levels. The concept of the Virtual Management Operations Center has taken shape, grown, and has been well received by parties from a wide variety of agencies and organizations in the Finger Lakes region and beyond. As it has evolved in design and functionality, and to better illustrate its current focus for this project, it has been given the expanded name of Watershed Virtual Management Operations Center (W-VMOC). It offers the advanced, compelling functionality of interactive 3D visualization interfaced with 2D mapping, all accessed via Internet or virtually any kind of distributed computer network. This strong foundation will allow the development of a Decision Support System (DSS) with anticipated enhanced functionality to be applied to the myriad issues involved in the wise management of the Finger Lakes region.

Brower, Robert↗
DOE OSTI2020

TorchBraid

Torchbraid is a python package designed for interaction with the PyTorch library. It enables training of neural networks in a layer-parallel fashion.SAND2020-12228 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Cyr, Eric↗
DOE OSTI2023

AmeriFlux FLUXNET-1F US-xUN NEON University of Notre Dame Environmental Research Center (UNDE)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xUN NEON University of Notre Dame Environmental Research Center (UNDE). This is the FLUXNET version of the carbon flux data for the site US-xUN NEON University of Notre Dame Environmental Research Center (UNDE) produced by applying the standard ONEFlux (1F) software. Site Description - NEON's Domain 5 core site is located at the University of Notre Dame Environmental Research Center (UNDERC) East. Straddling the border between Northern Wisconsin and Michigan’s Upper Peninsula, the UNDERC property comprises approximately 7500 acres and is maintained as an environmental education and research facility. UNDERC also has 30 lakes comprising 1350 acres, including Crampton Lake, a NEON aquatics site. Region-wide logging for pine in the late 1800s and early to mid-1900's led to clear cutting of most forested areas on the property. The main parcel was donated to the University in the 1930s. Timber harvest continued into the 1950s and later, leaving a mixture of successional forest regrowth. Since the 1970s, the site has been minimally managed to maintain access for recreational, educational and research goals.

Network), NEON (National Ecological Observatory↗
DOE OSTI2020

Robust and resilient coordination of feeders with uncertain distributed energy resources: from real-time control to long-term planning

To enable flexible demand and ensure reliable and economical operation of distribution systems, we present a novel hierarchical scheme that actively coordinates responsive behind-the-meter grid resources, including distributed energy resources (DERs), to reliably manage each unbalanced distribution feeder and exploits the available flexibility to economically optimize the entire network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

14 SOLAR ENERGY↗
DOE OSTI2022

Schema Elements for Granta Annual Report: FY2022

Granta: Materials Intelligence, also known as Granta:MI or Granta, is a commercial database software by Ansys, Inc. that is utilized by the Nuclear Security Enterprise (NSE) to organize and store relevant materials data. For a complete discussion of the use of Granta:MI at NSE sites, see the FY21 annual report. Granta:MI is used by five NSE sites locally, and all NSE sites have access to an enterprise instance on the Enterprise Secure Network (ESN) as well as an unclassified development instance. It has been recognized by NNSA management that a shared repository for additive manufacturing (AM) data would not only ensure data and knowledge is not lost but would provide a pool of information relating AM inputs (build parameters, raw materials properties, post-processing information) to the as-built properties of AM parts. Such a pool of data would enable optimization of AM build design and help NNSA achieve the goals of shortening fielding times for new components.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Final Report DE-FE0031785 Mohsen Ahmadian, Ph.D. Demonstration of Proof of Concept of a Multiphysics Approach for Real-Time Remote Monitoring of Dynamic Changes in Pressure and Salinity in Hydraulically Fractured Networks

Hydraulic fracturing has evolved into a multistep process with varying flow rates, carrier fluids (e.g., gel or slickwater), proppant loadings, and proppant grain sizes. As a result, primary recovery from a hydraulically fractured tight-oil reservoir is often a tiny fraction of the original oil in place, ranging between 5 and 10%. As stated in the FOA1990, “part of this problem is due to the inability of current well completion processes to effectively stimulate the entire reservoir volume in contact with the wellbore. Innovative technologies are needed that can help improve the effectiveness of reservoir completion methods, maximize stimulated reservoir volumes, and optimize recovery over the entire producing life span of a well”. We first need to enhance the current fracture diagnostic techniques to improve a well-completion design. However, detecting and delineating a subsurface hydraulic fracture is extremely difficult because the induced fracture network is only fractionally propped, and these propped fractures are generally very thin. Microseismic and tiltmeter monitoring techniques can provide information on the fracture extent but provide little or no information on the movement and final distribution of proppant or production fluids. On the other hand, electromagnetic (EM) imaging has shown the capability to monitor proppant distribution throughout the fracture area, especially in the presence of Electrically Active Proppants (EAPs). A previous EM survey of hydraulic fracturing at the Devine Fracture Pilot Site (DFPS) and subsequent EM code developments demonstrated this survey as a robust technique to remotely interrogate the extent of the EAP-filled hydraulic fracture during its propagation. The objectives of the project were threefold: (1) to capitalize on the material properties of an EAP to demonstrate remote monitoring of relative changes in pressure, pressure, and flow that are commonly encountered during production from a hydraulically fractured reservoir; (2) to evaluate EM imaging tools, to achieve Objective 1 in near real-time; and (3) to develop a multi-physics joint inversion approach to precisely predict flow patterns and physiochemical changes within an EAP-filled fracture network. This research project was built upon our previous work at the Devine Test Site managed by the Bureau of Economic Geology (BEG) at The University of Texas at Austin (UT-Austin). It also leveraged a significant investment from the Advanced Energy Consortium (AEC) to address the DOE's interest in subsurface flow, containment, and characterization by multiple signals. This three-year and three-month project succeeded in demonstrating the feasibility of a real-time dynamic fluid flow mapping technique at Technology Readiness Level 5 (TRL5) by utilizing a commercially available surface-based Controlled-Source Electromagnetic (CSEM) method (Objectives 1, 2). We demonstrated that injections into an EAP-filled fracture could be successfully coupled with real-time electric field measurements on the surface, leading to remote monitoring of dynamic changes within the EAP-filled fracture. Furthermore, the observed electric field in our study is influenced by bottomhole pressure, flow rate, and salinity, which is demonstrated by comparing these parameters with the electrical field potentials. EM simulations solely based on assumptions of fracture conductivity changes during injection did not reproduce the whole measured electric field magnitudes. Preliminary estimates showed that including Streaming Potential (SP) in our geophysical model is likely needed to reduce the simulation misfit.

02 PETROLEUM↗
NASA NTRS1992

The application of integrated knowledge-based systems for the Biomedical Risk Assessment Intelligent Network (BRAIN)

One of NASA's goals for long duration space flight is to maintain acceptable levels of crew health, safety, and performance. One way of meeting this goal is through BRAIN, an integrated network of both human and computer elements. BRAIN will function as an advisor to mission managers by assessing the risk of inflight biomedical problems and recommending appropriate countermeasures. Described here is a joint effort among various NASA elements to develop BRAIN and the Infectious Disease Risk Assessment (IDRA) prototype. The implementation of this effort addresses the technological aspects of knowledge acquisition, integration of IDRA components, the use of expert systems to automate the biomedical prediction process, development of a user friendly interface, and integration of IDRA and ExerCISys systems. Because C language, CLIPS and the X-Window System are portable and easily integrated, they were chosen ss the tools for the initial IDRA prototype.

Loftin, Karin C.↗
NASA NTRS1993

NASA Langley Research Center's distributed mass storage system

There is a trend in institutions with high performance computing and data management requirements to explore mass storage systems with peripherals directly attached to a high speed network. The Distributed Mass Storage System (DMSS) Project at NASA LaRC is building such a system and expects to put it into production use by the end of 1993. This paper presents the design of the DMSS, some experiences in its development and use, and a performance analysis of its capabilities. The special features of this system are: (1) workstation class file servers running UniTree software; (2) third party I/O; (3) HIPPI network; (4) HIPPI/IPI3 disk array systems; (5) Storage Technology Corporation (STK) ACS 4400 automatic cartridge system; (6) CRAY Research Incorporated (CRI) CRAY Y-MP and CRAY-2 clients; (7) file server redundancy provision; and (8) a transition mechanism from the existent mass storage system to the DMSS.

Pao, Juliet Z.↗