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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cyber Secure Sensor Network for Fossil Fuel Power Generation Assets Monitoring

The energy sector is undergoing digital transformation which is to say more and more power generation assets have become automated and connected to the internet. The connected sensors can tap into plants to monitor the health of assets and manage fleets remotely. These are just some of the benefits digitalization is bringing to the power industry. Within a power plant, control systems are no longer concerned with one system or one piece of equipment, but rather whole fleet of assets inter-connected with smart sensors which have the function of continuously monitoring and transmitting real-time operational data to operators. These connected systems will form a part of the industrial internet of things (IIoT). The big data scenarios provide benefits of performing system prognostics and optimization which is a key selling point of power plant digitalization.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2012

Mars Express Forward Link Capabilities for the Mars Relay Operations Service (MaROS)

This software provides a new capability for landed Mars assets to perform forward link relay through the Mars Express (MEX) European Union orbital spacecraft. It solves the problem of standardizing the relay interface between lander missions and MEX. The Mars Operations Relay Service (MaROS) is intended as a central point for relay planning and post-pass analysis for all Mars landed and orbital assets. Through the first two phases of implementation, MaROS supports relay coordination through the Odyssey orbiter and the Mars Reconnaissance Orbiter (MRO). With this new software, MaROS now fully integrates the Mars Express spacecraft into the relay picture. This new software generates and manages a new set of file formats that allows for relay request to MEX for forward and return link relay, including the parameters specific to MEX. Existing MEX relay planning interactions were performed via email exchanges and point-to-point file transfers. By integrating MEX into MaROS, all transactions are managed by a centralized service for tracking and analysis. Additionally, all lander missions have a single, shared interface with MEX and do not have to integrate on a mission-by mission basis. Relay is a critical element of Mars lander data management. Landed assets depend largely upon orbital relay for data delivery, which can be impacted by the availability and health of each orbiter in the network. At any time, an issue may occur to prevent relay. For this reason, it is imperative that all possible orbital assets be integrated into the overall relay picture.

Allard, Daniel A.↗
DOE OSTI2022

Reliability and Integrity Management Program Implementation Approach

Nuclear energy is the most reliable and environmentally sustainable energy source available today. In the United States, nuclear-generated power accounts for approximately 20% of total electricity and over 55% of clean energy. New advanced reactors have enormous potential to help further decarbonize the energy market, enhance grid resiliency, create new jobs, and build a stronger economy. More than 50 new reactors are being developed in the United States, and the federal government realizes an urgent need to deploy nuclear technologies to meet the country’s energy, environmental, and national security goals. As such, the U.S. Department of Energy launched multiple programs to support advanced reactor deployment. The research described in this paper explores implementation strategies for the Reliability and Integrity Management Program that directly supports the U.S. Department of Energy goal to enable the near-term deployment of the advanced reactor technologies. The project is conducted under the Regulatory Development Program for advanced reactors sponsored by the U.S. Department of Energy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗
DOE OSTI2026

Generative large language models for predictive maintenance planning

Maintenance planning and the generation of necessary components for tasks can prove time-consuming and complex. Automating the creation of recurring or similar tasks by leveraging previous planning packages and data, while uncovering insights to automate planning package generation, presents an opportunity to conserve valuable time and resources. This work aims to harness the textual and probabilistic capabilities of large language models (LLMs) to automate the generation of planning packages. Utilizing diverse data sources ranging from raw data to handwritten text, both singular and collaborative LLMs are trained and tested. Results demonstrate their capability to generate essential planning package components, effectively replicating the statistical patterns in the data. This demonstrates the use of these tools inside a digital asset for automated planning. This work outlines a methodology for constructing datasets, a training suite, and evaluation methods for LLM-based textual and conversational planning tools utilized in an asset digital twin. Results indicate that the fine-tuned models generate estimated planning information within the statistical ranges observed in real maintenance data. The models achieve high accuracy (>90%) in document question-answering and instruction generation tasks. Furthermore, the conversational retrieval-augmented generation (RAG) assistant system achieves 100% document retrieval accuracy, while conversational information capture exceeds 98% across the majority of work-package assistant modules.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Evaluating Water Assets Using Water Efficiency Framework for Infrastructure Intensive Agency

Water infrastructure-intensive organizations should incorporate sustainability principles when making decisions on infrastructure investments to ensure the long-term resilience of mission-critical equipment and components. A water efficiency evaluation framework to inform infrastructure investments is discussed and applied to three federal campuses. The methodology considered emphasizes the iterative process between data analysis and decision-making; evaluates cost-sharing solution alternatives when making final recommendations; considers both internal and external stakeholder perceptions of project outcomes and future planning; and makes explicit government and community preferences when evaluating projects. Case study findings underscore condition evaluations for infrastructure that are critical to setting a baseline for system performance and determining desired potential upgrades and sustainment strategies. Such a holistic approach has demonstrated effectiveness for understanding, classifying, and recommending innovative water asset solutions that are necessary for the public sector to consider in today’s complex, modern planning environment.

Asset Management, Alternative Water, evaluation, P↗
DOE OSTI2015

Interconnection Assessment Methodology and Cost Benefit Analysis for High-Penetration PV Deployment in the Arizona Public Service System

In an effort to better understand the impacts of high penetrations of photovoltaic (PV) generators on distribution systems, Arizona Public Service and its partners completed a multi-year project to develop the tools and knowledge base needed to safely and reliably integrate high penetrations of utility- and residential-scale PV. Building upon the APS Community Power Project-Flagstaff Pilot, this project investigates the impact of PV on a representative feeder in northeast Flagstaff. To quantify and catalog the effects of the estimated 1.3 MW of PV that will be installed on the feeder (both smaller units at homes and large, centrally located systems), high-speed weather and electrical data acquisition systems and digital 'smart' meters were designed and installed to facilitate monitoring and to build and validate comprehensive, high-resolution models of the distribution system. These models are being developed to analyze the impacts of PV on distribution circuit protection systems (including coordination and anti-islanding), predict voltage regulation and phase balance issues, and develop volt/VAr control schemes. This paper continues from a paper presented at the 2014 IEEE PVSC conference that described feeder model evaluation and high penetration advanced scenario analysis, specifically feeder reconfiguration. This paper presents results from Phase 5 of the project. Specifically, the paper discusses tool automation; interconnection assessment methodology and cost benefit analysis.

14 SOLAR ENERGY↗
DOE OSTI2015

Total Dissolved Gas Prediction and Optimization in RIVERWARE

Management and operation of dams within the Columbia River Basin (CRB) provides the region with irrigation, hydropower production, flood control, navigation, and fish passage. These various system-wide demands can require unique dam operations that may result in both voluntary and involuntary spill, thereby increasing tailrace levels of total dissolved gas (TDG) which can be fatal to fish. Appropriately managing TDG levels within the context of the systematic demands requires a predictive framework robust enough to capture the operationally related effects on TDG levels. Development of the TDG predictive methodology herein attempts to capture the different modes of hydro operation, thereby making it a viable tool to be used in conjunction with a real-time scheduling model such as RiverWare. The end result of the effort will allow hydro operators to minimize system-wide TDG while meeting hydropower operational targets and constraints. The physical parameters such as spill and hydropower flow proportions, accompanied by the characteristics of the dam such as plant head levels and tailrace depths, are used to develop the empirically-based prediction model. In the broader study, two different models are developed a simplified and comprehensive model. The latter model incorporates more specific bubble physics parameters for the prediction of tailrace TDG levels. The former model is presented herein and utilizes an empirically based approach to predict downstream TDG levels based on local saturation depth, spillway and powerhouse flow proportions, and entrainment effects. Representative data collected from each of the hydro projects is used to calibrate and validate model performance and the accuracy of predicted TDG uptake. ORNL, in conjunction with IIHR - Hydroscience & Engineering, The University of Iowa, carried out model adjustments to adequately capture TDG levels with respect to each plant while maintaining a generalized model configuration. Validation results indicate excellent model performance with coefficient of determination values exceeding 92% for all sites. This approach enables model extension to an increasingly wider array of hydropower plants, i.e., with the proper data input, TDG uptake can be calculated independent of actual physical component design. The TDG model is used as a module in the systematic optimization framework of RiverWare, a river and reservoir modeling tool used by federal agencies, public utility districts, and other dam owners and operators to forecast, schedule, and manage hydropower assets. The integration and testing of the TDG module within RiverWare, led by University of Colorado's Center for Advanced Decision Support for Water and Environmental Systems (CADSWES), will allow users to generate optimum system schedules based on the minimization of TDG. Optimization analysis and added value will be quantified as system wide reductions in TDG achieved while meeting existing hydropower constraints. Future work includes the development of a method to predict downstream reservoir forebay TDG levels as a function of upstream reservoir tailrace TDG values based on river hydrodynamics, hydro operations, and reservoir characteristics. Once implemented, a holistic model that predicts both TDG uptake and transport will give hydropower operators valuable insight into how system-wide environmental effects can be mitigated while simultaneously balancing stakeholder interests.

13 HYDRO ENERGY↗
DOE OSTI2016

Functional Requirements for an Electronic Work Package System

This document provides a set of high level functional requirements for a generic electronic work package (eWP) system. The requirements have been identified by the U.S. nuclear industry as a part of the Nuclear Electronic Work Packages - Enterprise Requirements (NEWPER) initiative. The functional requirements are mainly applied to eWP system supporting Basic and Moderate types of smart documents, i.e., documents that have fields for recording input such as text, dates, numbers, and equipment status, and documents which incorporate additional functionalities such as form field data “type“ validation (e.g. date, text, number, and signature) of data entered and/or self-populate basic document information (usually from existing host application meta data) on the form when the user first opens it. All the requirements are categorized by the roles; Planner, Supervisor, Craft, Work Package Approval Reviewer, Operations, Scheduling/Work Control, and Supporting Functions. The categories Statistics, Records, Information Technology are also included used to group the requirements. All requirements are presented in Section 2 through Section 11. Examples of more detailed requirements are provided for the majority of high level requirements. These examples are meant as an inspiration to be used as each utility goes through the process of identifying their specific requirements. The report’s table of contents provides a summary of the high level requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Criticality Analysis of a Water Distribution System Considering Both Economic Consequences and Hydraulic Loss Using Modern Portfolio Theory

This study introduces an approach using Modern Portfolio Theory (MPT) to consider hydraulic resilience and economic consequence resilience of a water distribution system (WDS) to identify critical assets. ECLIPS (Economic Consequence Linked to Interruption in Providing Service), a way to represent loss of water provision as economic loss, is used to measure economic consequence following a reduction of WDS functionality. The approach is demonstrated using a hypothetical WDS and tested for pipe breakage and replacement scenarios using EPANET hydraulic simulations. First, the correlation between hydraulic resilience and economic consequence resilience was investigated to assess differences between two resilience measures for identifying pipe’s criticality for replacement. The results confirmed the two resilience measures exhibited differing responses (covariance = 0.2), suggesting that use of both would provide complementary insight. Results of the MPT analysis identified the benefits of balancing hydraulic and economic consequence resilience measures to yield lower risk. This study provides a practical approach to incorporate economic consequence into planning, design, and research applications identifying critical WDS assets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1991

Design concepts for integrating the IMKA technology with CLIPS

The author shares his experiences in evaluating the technical alternatives for integrating the Initiative for Managing Knowledge Assets (IMKA) frame-based knowledge acquisition system with the C language Integrated Production System (CLIPS). Integrating the IMKA technology with CLIPS allows application knowledge to be encoded naturally, using both frames and rules, and allows the knowledge stored in frames to be reasoned about using rules. An overview is given in viewgraph form of the features of the IMKA technology. The challenges of integrating the IMKA technology with CLIPS, three integration models, and the circumstances under which each is appropriate are discussed.

Scarola, David↗
DOE OSTI2016

Creating an Energy Intelligent Campus: Data Integration Challenges and Solutions at a Large Research Campus

Rich, well-organized building performance and energy consumption data enable a host of analytic capabilities for building owners and operators, from basic energy benchmarking to detailed fault detection and system optimization. Unfortunately, data integration for building control systems is challenging and costly in any setting. Large portfolios of buildings--campuses, cities, and corporate portfolios--experience these integration challenges most acutely. These large portfolios often have a wide array of control systems, including multiple vendors and nonstandard communication protocols. They typically have complex information technology (IT) networks and cybersecurity requirements and may integrate distributed energy resources into their infrastructure. Although the challenges are significant, the integration of control system data has the potential to provide proportionally greater value for these organizations through portfolio-scale analytics, comprehensive demand management, and asset performance visibility. As a large research campus, the National Renewable Energy Laboratory (NREL) experiences significant data integration challenges. To meet them, NREL has developed an architecture for effective data collection, integration, and analysis, providing a comprehensive view of data integration based on functional layers. The architecture is being evaluated on the NREL campus through deployment of three pilot implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Overview of JAXA and NASA Collaboration on Manned and Unmanned Aircraft Operations Integration in Disaster Response

Natural disasters have increased in frequency and intensity. With that increase has come an increased focus on improving disaster response efforts. As part of this focus, the Japan Aerospace Exploration Agency (JAXA) and the National Aeronautics and Space Administration (NASA) have been in collaboration since 2016 to explore improved airspace management for disaster response through the integration of manned aircraft and small Unmanned Aircraft Systems (UAS). The approach to this integration has been through leveraging JAXA’s Disaster Relief Aircraft Information Sharing Network (D-NET) system for the coordinated management of manned aircraft assets combined with NASA’S UAS Traffic Management (UTM) system for the management of UAS assets. To drive the innovation in improved response, JAXA and NASA have successfully connected respective systems and conducted a series of live flight tests first as part of a large-scale disaster drill and later in dedicated research flights. In each case, the D-NET and UTM systems were connected and exchanged data in real-time, which supported the planning and tracking of manned and unmanned operations. Through these test events, a number of key findings were derived through data analysis and stakeholder interviews with respect to the improvements offered by the integrated systems as well as key considerations for situation awareness of pilots regarding other operations in the airspace and flight path management.

disaster response↗
DOE OSTI2020

Complementary workflows for identifying one-hop network behavior and multi-hop network dependencies

A network analysis tool evaluates network flow information in complementary workflows to identify one-hop behavior of network assets and also identify multi-hop dependencies between network assets. In one workflow (e.g., using association rule learning), the network analysis tool can identify significant one-hop communication patterns to and/or from network assets, taken individually. Based on the identified one-hop behavior, the network analysis tool can discover patterns of similar communication among different network assets, which can inform decisions about deploying patch sets, mitigating damage, configuring a system, or detecting anomalous behavior. In a different workflow (e.g., using deep learning or cross-correlation analysis), the network analysis tool can identify significant multi-hop communication patterns that involve network assets in combination. Based on the identified multi-hop dependencies, the network analysis tool can discover functional relationships between network assets, which can inform decisions about configuring a system, managing critical network assets, or protecting critical network assets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Predictive Analytics for Hydropower Fleet Intelligence

A primary challenge in hydropower industry is the ability to maintain cost-competitiveness, reliability, and security of hydropower assets through evolving power system contexts and aging of the fleet. Maintaining cost-effective and reliable operations under these conditions is expected to require new modernization and maintenance paradigms for changing contexts. Changes in existing practices for O&M will require an understanding of the current state and health of hydropower assets, and the impact of changing paradigms on asset health and reliability. The Hydropower Fleet Intelligence project is developing and evaluating standardized methodologies and analysis tools for data-driven asset reliability and management technologies for hydropower, leading to eventual predictive maintenance planning, repair/replacement decision making, and asset-reliability and cost-optimized operations. A key question is the feasibility of using existing data sets at hydropower facilities to perform assessments of asset reliability. This document uses data from hydropower facilities to assess the potential for using available analytics methods for asset reliability estimates. In addition to reliability assessments, the feasibility of using existing analytics techniques for several other potential applications is discussed. Finally, a case study that a data-driven model is trained to learn nominal operations via vibration data from an asset of a certain plant, and then utilized to identify anomalies on a similar asset from a different plant, highlighting the generic use of proposed Prognostics and Health Management (PHM) approaches.

Yucesan, Yigit↗
DOE OSTI2016

Technology Maturation in Support of DOE 413.3B Project Execution - 16436

The DOE Order 413.3B 'Program and Project Management for the Acquisition of Capital Assets' provides program and project management direction for the acquisition of capital assets with the goal of delivering projects within the original performance baseline (PB), cost and schedule, and fully capable of meeting mission performance, safeguards and security, and environmental, safety, and health requirements. Execution of complex DOE 413.3B projects depends, in part, upon the successful integration of a technology maturation program. The Low Activity Waste Pre-Treatment System (LAWPS) is executing a detailed technology maturation program under the Technology Readiness Level/Technology Maturation Plan (TRL/TMP) guidance of DOE Order 413.3B. The interaction of the technology maturation process and the project execution including technical, programmatic, and contractual execution, has been a critical component for project success. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗