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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Routing and Infrastructure simulation for Shared Electric vehicles (RISE)

FERIS is an agent-based model that simulates the activity of a fleet of electric taxis in a metropolitan area. Agent activities include serving trips, rebalancing to anticipate future demand, and relocating to charge. The modeling framework allows researchers to study the impact of different routing algorithms, battery range, and charging infrastructure on fleet performance, energy consumption, environmental impact, and cost of service.

Bauer, Gordon↗
DOE OSTI2021

Infrastructure Expression: Discovery Tools

The Infrastructure Expression: Discovery Tools is a toolset that allows for the automated collection of various network, hardware, and software vulnerabilities and details to be collected from systems on a given network. These details are then converted into a STIX 2.1 format, allowing for easy viewing in existing applications as well as sharing and interfacing with tools that already use the STIX 2.1 format.

Cutshaw, Michael↗
DOE OSTI2021

Multiscale Machine-Learned Modeling Infrastructure Core

MuMMI Core is the central component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback across three scales of resolution.

Bhatia, Harsh↗
DOE OSTI2021

Multiscale Machine-Learned Modeling Infrastructure RAS

MuMMI RAS is the application component of the Multiscale Machine-Learned Modeling Infrastructure (MuMMI). It simulates RAS protein interactions at three scales of resolution coupled with ML-based selection and in-situ feedback. MuMMI RAS is particularly configured for massive scale, running thousands of simultaneous jobs with several terabytes of data on Lassen and Summit.

Moon, JosephY.↗
DOE OSTI2023

Data Science Infrastructure SOFTWARE

LANL science workflows generate complex data sets and ensembles of data requiring significant compute and storage resources. The Data Science Infrastructure (DSI) project focuses on data-driven approaches to make data more readily available to LANL projects. DSI workflows leverage metadata stored in data-agnostic databases, supported by an abstraction layer API to simplify searching and accessing data across simulation runs, experimental runs, filesystems and environments. The abstraction layer API allows the user to query a range of data types: raw output, processed data, configuration data, machine learning models, performance data, etc. In addition to the abstraction backend API, the DSI project is developing client-driven query APIs and UIs to support specific user workflows.

Turton, Terece↗
DOE OSTI2024

Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) Model

The Behind-the-meter Infrastructure Costs for Electrification Progression (BICEP) model quantifies the behind-the-meter (BTM) electrical upgrades required for decarbonization through electrification by comparing the expected change in capacity requirements from the electrification technologies to the existing capacity in distributed energy resources (DER) stock (including buildings).

Yoder, Tim↗
DOE OSTI2026

Data Files for 'The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure'

This data set includes modeling results from The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure, including region-specific (i.e., national, state, and core-based statistical area cities and towns) electric vehicle supply equipment port count requirements in 2025 and 2030 for multiple scenarios described in the study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database

The Advanced Infrastructure Integrity Modeling (AIIM) Onshore Pipeline Database is an interoperable spatial resource containing critical environmental, operational, and reported stressors tied to publicly available oil and gas pipeline locations across the contiguous U.S. and Alaska. This database contains two layers: 1. Pipeline point locations (‘pipeline_points’) – More than 500,000 points (at every kilometer along pipelines, and end points) to which more than 350 stress-related variables have been appended. 2. Merged pipelines (‘merged_pipelines’) – The original, publicly available pipeline data (see table below) merged together into one feature class.

Carbon Transport↗
DOE OSTI2018

Facilities & Infrastructure Five-Year Investment Plan

The Facilities & Infrastructure (F&I) Five-Year Investment Plan (Five-Year Plan) presents a framework to acquire, maintain, modify, and dispose real property assets with indirect and direct-funded investments to sustain and modernize Sandia's F&I portfolio. This plan begins with a description of the principles used to guide decision-making for indirect-funded investments followed by a high—level view of F&I investments planned in the near— and mid—terms to meet emerging F&I needs required to support current and future mission work across Sandia's campuses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Laboratory Agenda 2018: Changing the world's energy future and securing our critical infrastructure

Idaho National Laboratory (INL) has a vision of changing the world’s energy future and securing our nation’s critical infrastructure. INL’s mission involves discovering, demonstrating, and securing innovative nuclear energy solutions and other clean energy sources. The Laboratory also has a mission focused on protecting the nation’s power grids and other vital systems against man-made and natural threats. Completing our mission and fulfilling our vision requires carefully charting our path and priorities, building and strengthening our core capabilities, focusing on key research and development (R&D) and mission-support initiatives, assessing our performance, and correcting our priorities when necessary. INL’s Laboratory Agenda articulates INL’s priorities, goals, and initiatives to deliver our mission and vision efficiently, effectively, and collaboratively. It describes our commitment to simultaneous excellence in science and technology, management and operations, and community service, and sets priorities for Laboratory investments.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Fuel Cell Vehicle Infrastructure Research and Demonstration: Cooperative Research and Development Final Report, CRADA Number CRD-16-601

In support of NREL's mission, which includes preparing technologies and markets with 'speed and scale,' HATCI will loan up to two fuel cell vehicles (collectively, the 'vehicles') to NREL. Operation of the vehicles enables NREL to provide education of the vehicle technology and research renewable hydrogen production, fueling equipment, and hydrogen energy system integration in real-world conditions and use. These vehicles provide an opportunity for NREL to evaluate the Hydrogen Infrastructure Testing & Research Facility (HITRF) using a variety of vehicle types, which provides a balanced portfolio of this technology and represents real world conditions more accurately.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Building a Single Sign-On System for the Department of Homeland Security's Infrastructure Protection Gateway

The IP Gateway is an interface used by the Department of Homeland Security to collect and manage infrastructure information about communities across the nation. DHS currently depends on a third-party to manage the login system of the IP Gateway; however, in order to provide more consistent service to IP Gateway users, they contracted with INL to develop a new single sign-on system.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Open MPI Testing Infrastructure Update - September, 2019

Since the last update on the Open MPI regression testing infrastructure, and the deployment of the MTT Python client on more DOE HPC centers, problems with the client and its interaction with the community PostGreSQL database server at AWS began to appear. In particular, problems were found with the reporting of failed and timed out tests to the community database.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Gas-Electrical Grid Coordination for Cross Infrastructure Resilience Enhancement

An electric power grid is exceedingly faced with extreme events, such as physical attacks and natural disasters. In comparison, the underground natural gas pipeline-based transportation network is considered less vulnerable to such environmental threats. We consider that the overhead power transmissions can be hardened by replacing segments of electric power system with underground natural gas pipelines as an energy transportation system to counter effect extreme events which can damage interdependent infrastructures severely. This project investigates an extension of the power system planning problem considering extreme events and identifies the feasibility of solving this problem with advanced modeling and optimization methods. The proposed planning framework is formulated as a two-stage optimization problem. It is found that the integrated planning introduces the additional cost of pipeline planning and the operation constraints into the power system planning. However, gas pipelines are generally less exposed to extreme events, which can provide a more resilient power transmission for supplying the electrical loads. It is with this potential for enhancing the power grid resilience that the proposed integrated expansion of electricity and natural gas system is considered an optimal layout for the transportation of energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

OpenK: An Open Infrastructure for the Accumulation, Sharing and Reuse of High Performance Computing Knowledge

In high performance computing (HPC), often a wide range of knowledge about the particular domains, software applications, and hardware architectures are necessary for applying the right optimizations in the appropriate contexts. In today’s practice, however, such knowledge has been expressed and managed in an ad-hoc manner by each individual. Systematic accumulation, sharing and reuse of the knowledge across a broad community has been difficult. This paper introduces OpenK, an ontology-based open infrastructure for solving the problem. By centering around ontology – a generic knowledge representation – and extensible designs, it offers a promising support for lowering the barriers.

97 MATHEMATICS AND COMPUTING↗