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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 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Natural gas maximal load delivery for multi-contingency analysis

An increasing dependence on natural gas has amplified existing vulnerabilities to the power grid, including disruptions to gas transmission networks from natural and man-made disasters. To address the operational challenges arising from these disruptions, we, in this study, consider the problem of estimating the steady-state operating capacity of a damaged gas pipeline network while ensuring the maximal delivery of load. Specifically, we formulate the mixed-integer nonconvex maximal load delivery (MLD) problem, which proves difficult to solve on large-scale networks. To address this challenge, we present a relaxation of the MLD problem and use it to determine bounds on the transport capacity of a gas pipeline system. A rigorous computational evaluation over network models ranging in size from 11 to 4,197 junctions shows that the relaxation-based method is suitable for analyzing the impacts of multi-contingency network disruptions, often converging to the optimal solution of the relaxation in less than ten seconds.

03 NATURAL GAS↗

DOE OSTI2022

Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms

Wash vehicles containing either high- or low-pressure water sprayers, a collection of rotating brushes, or a combination of these, are frequently utilized in concentrating solar power (CSP) plants to maintain a high level of optical efficiency in the solar field. In recent years, multiple modeling approaches have been developed to obtain fleet sizes and mirror-washing schedules that optimize the tradeoff of vehicle capital and use costs and labor versus lost revenues due to soiling. These planning models cover normal operating conditions well but do not consider rare events such as dust storms which can cause a significant reduction in receiver productivity, or shut down operations until most or all of the solar field's mirrors have been cleaned. To that end, we propose a methodology that evaluates whether additional capital should be deployed to hedge against these events by weighing the net present value of the expected benefits against the capital costs. The output of this method is a breakeven frequency, a metric we sue to determine whether an additional vehicle should be purchased to address the contingency of dust storms by comparing it to the expected annual storm frequency We develop a small collection of case studies using commercial-scale CSP tower plants and obtain breakeven frequencies that mostly fall between 0.1 and 1.0 storms per year, depending on the existing fleet size and storm severity.

concentrating solar power↗

DOE OSTI2019

The allocation of a variable series reactor considering AC constraints and contingencies

The Variable Series Reactors (VSRs) can efficiently control the power flow through the adjustment of the line reactance. When they are appropriately allocated in the power network, the transmission congestion and generation cost can be reduced. Our work proposes a planning model to optimally allocate VSRs considering AC constraints and multi-scenarios including base case and contingencies. The planning model is originally a non-convex large scale mixed integer nonlinear program (MINLP), which is generally intractable. The proposed Benders approach decomposes the MINLP model into a mixed integer linear program (MILP) master problem and a number of nonlinear subproblems. Numerical case studies based on IEEE 118-bus demonstrate the high performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

A Methodology for Evaluating Operator Usage of Machine Learning Recommendations for Power Grid Contingency Analysis

This work presents the application of a methodology to measure domain expert trust and workload, elicit feedback, and understand the technological usability and impact when a machine learning assistant is introduced into contingency analysis for real-time power grid simulation. The goal of this framework is to rapidly collect and analyze a broad variety of human factors data in order to accelerate the development and evaluation loop for deploying machine learning applications. We describe our methodology and analysis, and we discuss insights gained from a pilot participant about the current usability state of an early technology readiness level (TRL) artificial neural network (ANN) recommender.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2014

Contingency Trajectory Design for a Lunar Orbit Insertion Maneuver Failure by the Lunar Atmosphere Dust Environment Explorer (LADEE) Spacecraft

The purpose of this extended abstract is to present results from a failed lunar-orbit insertion (LOI) maneuver contingency analysis for the Lunar Atmosphere Dust Environment Explorer (LADEE) mission, managed and operated by NASA Ames Research Center in Moffett Field, CA. The LADEE spacecrafts nominal trajectory implemented multiple sub-lunar phasing orbits centered at Earth before eventually reaching the Moon (Fig. 1) where a critical LOI maneuver was to be performed [1,2,3]. If this LOI was missed, the LADEE spacecraft would be on an Earth-escape trajectory, bound for heliocentric space. Although a partial mission recovery is possible from a heliocentric orbit (to be discussed in the full paper), it was found that an escape-prevention maneuver could be performed several days after a hypothetical LOI-miss, allowing a return to the desired science orbit around the Moon without leaving the Earths sphere-of-influence (SOI).

Lunar Orbit Insertion↗

NASA NTRS2014

Contingency Trajectory Design for a Lunar Orbit Insertion Maneuver Failure by the LADEE Spacecraft

This paper presents results from a contingency trajectory analysis performed for the Lunar Atmosphere & Dust Environment Explorer (LADEE) mission in the event of a missed lunar-orbit insertion (LOI) maneuver by the LADEE spacecraft. The effects of varying solar perturbations in the vicinity of the weak stability boundary (WSB) in the Sun-Earth system on the trajectory design are analyzed and discussed. It is shown that geocentric recovery trajectory options existed for the LADEE spacecraft, depending on the spacecraft's recovery time to perform an Earth escape-prevention maneuver after the hypothetical LOI maneuver failure and subsequent path traveled through the Sun-Earth WSB. If Earth-escape occurred, a heliocentric recovery option existed, but with reduced science capacapability for the spacecraft in an eccentric, not circular near-equatorial retrograde lunar orbit.

LADEE↗

NASA NTRSDate not supplied

Dynamic Vehicle Assessment for Intelligent Contingency Management of Urban Air Mobility Vehicles

New algorithms will be required to ensure passenger and bystander safety during the expected era of autonomous urban air mobility (UAM) aircraft. This paper examines an approach for assessing the vehicle capability to fly itself and to complete a mission safely. The concepts combine elements of system identification, adaptive control, flight dynamics, envelope predictions, and handling qualities, as well as human pilot intuition. The approach is applied to a simulation of a generic distributed electric propulsion urban air mobility-type aircraft, which was developed under the NASA Transformational Tools and Technologies (TTT) project, Autonomous Systems / Intelligent Contingency Management subproject.

flight envelope↗

NASA NTRS2020

Intelligent Contingency Management for Urban Air Mobility

The third aviation revolution is seeking to enable transportation where users have access to immediate and flexible air travel; the users dictate trip origin, destination and timing. One of the major components of this vision is urban air mobility (UAM) for the masses. UAM means a safe and efficient system for vehicles to move passengers and cargo within a city. In order to reach UAM’s full market potential the vehicle will have to be autonomous. One of the primary challenges of autonomous flight is dealing with off-nominal events, both common and unforeseen; thus, intelligent contingency management (ICM) is one of the enabling technologies. In this context, the vehicle has to be aware of its internal state and external environment at all times, ascertain its capability and make decisions about mission completion or modification. All of these functions require data to model and assess the environment and then take actions based on these models. Necessarily, there is uncertainty associated with the data and the models generated from it. Since we are dealing with safety-critical systems, one of the main challenges of ICM is to generate sufficient data and to minimize its uncertainty to enable practical and safe decision making. We propose an overall architecture that incorporates deterministic and learning algorithms together to assess vehicle capabilities, project these into the future and make decisions on mission management level. A layered approach allows for mature parts and technologies to be integrated into early highly automated vehicles before the final state of autonomy is reached.

data-driven systems↗

NASA NTRSDate not supplied

Intelligent Contingency Management for Urban Air Mobility

UAM↗

NASA NTRSDate not supplied

Intelligent Contingency Management for Urban Air Mobility

UAM;↗

NASA NTRSDate not supplied

Automated Flight & Contingency Management (AFCM) Power Slide

This single slide presentation gives a summary of the Advanced Air Mobility (AAM) Automated Flight & Contingency Management (AFCM) subproject, at a high level for a potentially non-NASA technical audience.

Advanced Air Mobility↗

DOE OSTI2021

Wash Vehicle Fleet Sizing for Contingency Planning Against Dust Storms: Preprint

Wash vehicles containing either high- or low-pressure water sprayers, a collection of rotating brushes, or a combination of these, are frequently utilized in concentrating solar power (CSP) plants to maintain a high level of optical efficiency in the solar field. In recent years, multiple modeling approaches have been developed to obtain fleet sizes and mirror-washing schedules that optimize the tradeoff of vehicle capital and use costs and labor versus lost revenues due to soiling. These planning models cover normal operating conditions well but do not consider rare events such as dust storms which can a significant reduction in receiver productivity, or shut down operations until most or all of the solar field’s mirrors have been cleaned. To that end, we propose a methodology that evaluates whether additional capital should be deployed to hedge against these events by weighing the net present value of the expected benefits against the capital costs. The output of this method is a breakeven frequency, a metric we sue to determine whether an additional vehicle should be purchased to address the contingency of dust storms by comparing it to the expected annual storm frequency We develop a small collection of case studies using commercial-scale CSP tower plants and obtain breakeven frequencies that mostly fall between 0.1 and 1.0 storms per year, depending on the existing fleet size and storm severity.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2021

MARS 2020 Contingency Planning Overview

Case study on contingency planning for the MARS 2020 rover launch. Intended as part of a training for international consequence management personnel for IAEA and/or NATO-sponsored training classes. Funded through NA-81

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Neural Networks Ensembles to Accelerate Power Grid Contingency Analysis

Novel uncertainty quantification approach for machine learning based physics informed graph neural networks capable of quickly computing bulk energy system contingencies from a large search space with tolerance to changing grid topologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Contingency Contractor Optimization Phase 3 Sustainment Cost by JCA Implementation Guide

This document provides implementation guidance for implementing personnel group FTE costs by JCA Tier 1 or 2 categories in the Contingency Contractor Optimization Tool – Engineering Prototype (CCOT-P). CCOT-P currently only allows FTE costs by personnel group to differ by mission. Changes will need to be made to the user interface inputs pages and the database

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Severe Contingency Solver

Los Alamos researchers have developed the Severe Contingency Solver (SCS) to help power network operators and policy makers better understand the vulnerabilities of electric power transmission systems to extreme events, such as hurricanes, ice storms, and earthquakes. It guarantees a solution for power networks with hundreds to thousands of damaged components. SCS supports multiple platforms (e.g., Linux, Windows, Mac OS X) and removes the need for human intervention when analyzing severely damaged power networks. The information can be used to prepare for extreme events and plan network upgrades for improved network resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan

A Long Term Monitoring System Design has been designed to monitor conditions in the perched groundwater including changes in the perched aquifer as a result of implementing the response actions. Monitoring is required for verifying the effectiveness of perched groundwater response actions (i.e., conditions in the perched aquifer are being affected as intended) and for confirming that the perched aquifer and Ogallala Aquifer characterization as defined in the Resource Conservation and Recovery Act Facility Investigation Report and the Corrective Measure Studies/Feasibility Study remains accurate. If monitoring results obtained through the monitoring network identify an unexpected conditions or deviation, contingent actions will be considered and implemented as necessary to ensure continued protection of the Ogallala Aquifer and human health and the environment.

54 ENVIRONMENTAL SCIENCES↗