Search NASA⌕ Search

SEARCH · Search NASA

Results for “Infrastructure”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Construction-Scale Concrete Additive Manufacturing and its Application in Infrastructure Energy Storage

Construction is filled with labor intensive, hazardous, and often wasteful processes. It is also an enormous industry, so improvements in efficiency could have a tremendous economic impact. Construction-scale additive manufacturing is one path toward achieving those improvements. In this paper, a construction-scale additive manufacturing system, called Sky-BAAM, is presented. In addition to possibly leading to more energy-efficient construction practices, leveraging additive manufacturing in construction opens the solution space to more energy efficient building design. One such design, the EMPOWER wall, is also presented in this paper. The exterior of the wall is shaped to maximize heat transfer, while acting as form work for an internal energy-storage system. This allows energy to be stored in the wall during off-peak times and retrieved during peak periods.

Atkins, Celeste↗
DOE OSTI2024

Evaluation of Common Thermoplastic Polymers in High-Pressure Cycling Hydrogen Under Ambient and Cold Environments as Applicable to the Hydrogen Infrastructure

Thermoplastic polymers are required to perform unfailingly under stringent conditions of changing pressures (35 MPa to 70 MPa) and temperatures (-40°C to +85°C) in storage and fueling operations. Although diffusivity in glassy polymers appear to be an order of magnitude lower than elastomers, polymer microstructural attributes such as degree of crystallinity and presence of polar and non-polar groups on the main chain with and without branching can play a substantial role in influencing their behaviors in hydrogen environments. In the work described here, the effect of high-pressure hydrogen cycling on PEEK, PTFE, PA11, HDPE, POM (and different commercial grades of these polymers) under ambient and cold (-40°C) conditions is addressed. Ex-situ characterization for polymer changes included density measurements for impact of hydrogen retention, hardness changes using nanoindentation, storage modulus and glass transition changes using dynamic mechanical and thermal analysis (DMTA), degree of crystallization with Differential Scanning Calorimetry (DSC) and tensile testing following ASTM D412. In other evaluations, solid-state nuclear magnetic resonance (NMR), attenuated total reflectance Fourier transform infra-red spectroscopy (ATRFTIR), X-ray diffraction (XRD), and X-ray CT results are presented. The overall impact of these evaluations is to establish a technical basis for the behaviors of common thermoplastics in cycling hydrogen environments under ambient and cold temperatures while establishing the relationship between polymer structure-based properties and hydrogen transport effects.

Menon, Nalini C.↗
DOE OSTI2024

Cookie-Jar: An Adaptive Re-configurable Framework for Wireless Network Infrastructures

5G advancements like Massive Multiple Input Multiple Output (MIMO) bring high capacity and low latency, but also intensify interference challenges. Static and dynamic coordination techniques address this, often at the cost of increased power draw. We introduce Cookie-Jar (CJ), an interference coordination (IC) framework using reinforcement learning for multi-goal optimization. By dynamically adjusting network, power, and topology parameters based on real-time conditions, CJ improves Signal to Noise and Interference Ratio (SINR) while minimizing power consumption. Simulated 5G experiments showcase CJ's potential, achieving a 15% SINR improvement with near-identical power draw compared to existing methods.

Network↗
DOE OSTI2018

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS). LADS (Layout-Aware Data Scheduling) is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access) architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Hierarchical Engine for Large-scale Infrastructure Co-Simulation

HELICS is designed to support very-large-scale (100,000+ federates) cosimulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features include cross platform operating system support, the integration of both event driven (e.g., packetized communication) and time-series (e.g., power flow) simulations, and the ability to co-iterate among federates to ensure physical model convergence at each time step.

Source record↗
DOE OSTI2017

Hiearchical Engine for Large Scale Infrastructure Simulation

HELICS ls a new open-source, cyber-physlcal-energy co-simulation framework for electric power systems. HELICS Is designed to support very-large-scale (100,000+ federates) co­simulations with off-the-shelf power-system, communication, market, and end-use tools. Other key features Include cross platform operating system support, the integration of both eventdrlven (e.g., packetlzed communication) and time-series (e.g.,power flow) simulations, and the ability to co-Iterate among federates to ensure physical model convergence at each time step.

Top, Philip↗
DOE OSTI2020

Athena - Digital Twin and Infrastructure Model [SWR 20-106]

The software provides database access and analysis code for project ATHENA data. In particular, it provides (1) access to the AWS RDS database and (2) supporting code for analysis. Additionally, the software contains all the code related to modeling the Dallas-Fort Worth International Airport (DFW) curbside (CTA modeling) using SUMO simulator. It demonstrates how to install, run and derive useful data from SUMO simulations. We will describe the basic files needed to run a simulation and how those files are generated. The software also has code for generating simulations representing different traffic management policies for DFW and simulating those policies on personal computer or on NREL's Eagle supercomputer. The examples provided are a representation of the DFW airport for curbside dropoff and and pickup.

Severino, Joseph↗
DOE OSTI2022

Caldera Infrastructure Charge Module (ICM)

Caldera ICM is part of Caldera software platform, a suite of collective, open-source tools that was developed to improve the state of the art in modeling the impacts of Electric Vehicle (EV) charging on the grid. The foundation of Caldera ICM is it’s first-of-its-kind library of high-fidelity charging models for a wide variety of vehicles, validated by test data under a range of operating conditions. The charging models are used to accurately model the EV charging on an electric vehicle supply equipment (EVSE) – also known as a charger. ICM uses as inputs, the EV characteristics such as battery size, battery chemistry (i.e. NMC, LTO), watt hour per mile, inverter efficiency and max charge rate; as well as EVSE characteristics such as max current and supply equipment type (i.e. L2 vs XFC). Using these inputs Caldera ICM creates an uncontrolled charging profile curve for each compatible EV-EVSE pair. These charge profiles can be used stand alone to estimate charge duration given start State Of Charge (SOC) and end SOC or charge energy size given start SOC and charge duration. In Caldera Grid, another tool in the Caldera software platform, these charge profiles are used to represent EV charging as a load on the grid using charge event data such as EV type, SE type, start SOC, final SOC, park start time and park end time. ICM currently supports energy shifting Smart Charge Management (SCM) strategies such as "Time Of Use (TOU) immediate”, “TOU random” and “random start” by delaying the charge to start at a preferable time with respect to the strategy and, one voltage support SCM strategy named autonomous voltage control strategy by providing reactive power back to the electric grid.

Sundarrajan, ManojKumar Cebol↗
DOE OSTI2024

InfraSys (Infrastructure Systems) [SWR-24-42]

This package implements a data store for components and time series in support of Python-based modeling packages. While it is designed to support teams modeling transmission and distribution systems for electrical grids, it can be used by any package that needs to store components (e.g., generators and buses) that have quantities (e.g., power and voltage) which may vary over time. The package was inspired by InfrastructureSystems.jl (https://github.com/NREL-Sienna/InfrastructureSystems.jl).

Thom, Daniel↗