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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

The ARES High-level Intermediate Representation

The LLVM intermediate representation (IR) lacks semantic constructs for depicting common high-performance operations such as parallel and concurrent execution, communication and synchronization. Currently, representing such semantics in LLVM requires either extending the intermediate form (a signi cant undertaking) or the use of ad hoc indirect means such as encoding them as intrinsics and/or the use of metadata constructs. In this paper we discuss a work in progress to explore the design and implementation of a new compilation stage and associated high-level intermediate form that is placed between the abstract syntax tree and when it is lowered to LLVM's IR. This highlevel representation is a superset of LLVM IR and supports the direct representation of these common parallel computing constructs along with the infrastructure for supporting analysis and transformation passes on this representation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Initial CGE Model Results Summary Exogenous and Endogenous Variables Tests

The following discussion presents initial results of tests of the most recent version of the National Infrastructure Simulation and Analysis Center Dynamic Computable General Equilibrium (CGE) model developed by Los Alamos National Laboratory (LANL). The intent of this is to test and assess the model’s behavioral properties. The test evaluated whether the predicted impacts are reasonable from a qualitative perspective. This issue is whether the predicted change, be it an increase or decrease in other model variables, is consistent with prior economic intuition and expectations about the predicted change. One of the purposes of this effort is to determine whether model changes are needed in order to improve its behavior qualitatively and quantitatively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Hurricane Sandy Economic Impacts Assessment: A Computable General Equilibrium Approach and Validation

Economists use computable general equilibrium (CGE) models to assess how economies react and self-organize after changes in policies, technology, and other exogenous shocks. CGE models are equation-based, empirically calibrated, and inspired by Neoclassical economic theory. The focus of this work was to validate the National Infrastructure Simulation and Analysis Center (NISAC) CGE model and apply it to the problem of assessing the economic impacts of severe events. We used the 2012 Hurricane Sandy event as our validation case. In particular, this work first introduces the model and then describes the validation approach and the empirical data available for studying the event of focus. Shocks to the model are then formalized and applied. Finally, model results and limitations are presented and discussed, pointing out both the model degree of accuracy and the assessed total damage caused by Hurricane Sandy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks

The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

HPC for the EEC: Industrial Trade Tools for the Aging Energy Infrastructure

The petrochemical and refining sectors are challenged with reliably delivering safer and cleaner energy to US consumers, while meeting an ever-growing global demand. The petrochemical and refining infrastructure in the USA is aging, and corrosion and damage mechanisms are constant threats to mechanical integrity, safety, and profitability. However, governments and industry stakeholders are reluctant to replace or upgrade the existing infrastructure due to the immense cost. To better understand and mitigate the risks of aging energy infrastructure, strong technical analysis capabilities, combined with optimized monitoring and decision making, is critical. Today, this is accomplished via complex simulations and data analysis. To this end, advanced High-Performance-Computing (HPC) software will be leveraged and integrated in easy-to-use industrial trade tools, to lower the barrier for new users, increase the ease of access for experienced users, and allow for smarter decisions to be made in the midstream and downstream energy sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Expanded Capabilities and Opportunities for Virtual Beamline Code

In the 25 years since LLNL broke ground on the National Ignition Facility (NIF) - a cornerstone of the National Nuclear Security Administration’s Stockpile Stewardship Program - the NIF and Photon Science (NIF&PS) Directorate has steadily pushed the boundaries of laser physics, nonlinear optics, and photonics in service of inertial confinement fusion experiments, and advanced photon sources development. Beyond the 192 beamlines of the primary laser facility with its world-record energy and fusion yields, NIF&PS capabilities have expanded to include chirped-pulse amplification, kilojoule petawatt-class short-pulse systems to generate hard x-ray radiographic probes, high-average power lasers as secondary sources for generation or wake field particle acceleration along directed energy applications, and other scientific pursuits. The Computing Directorate partners with NIF&PS on numerous projects and technologies from diagnostic measurements and high performance control systems to data analysis, information technology infrastructure, and scientific simulation code development. “This strong collaboration enables cutting-edge science, particularly with regard to physics-based modeling and simulation,” says physicist Jean-Michel Di Nicola. One crucial capability for NIF&PS is the Virtual Beamline (VBL) laser simulation code. It can model all the major laser physics and technology involved in the design optimization, commissioning, and operations of advanced laser architectures from tabletop to NIF-scale. VBL provides researchers with high-fidelity models and high-resolution calculations of laser performance predictions—including for the entire NIF laser system, the Advanced Radiographic Capability, parts of the High Repetition-Rate Advanced Petawatt Laser System laser delivered to the Czech Republic, and the Optical Science Laser. After more than two decades of experimentally verified physics and computing enhancements, this unique workhorse code is wrapping up another major milestone: migration from Java to C++ with a flurry of user interface and optimization features, as well as laser physics and high-resolution enhancements thanks to parallel execution on Livermore Computing platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Evaluating GHG Mitigation Potential from ESPC Projects [Slides]

This report explores the impact of implemented ESPC projects on the projected greenhouse gas (GHG) emissions reductions in the U.S. buildings sector, and the associated projected annual cost savings and marginal abatement costs. It is important to investigate the role that energy retrofits can play in achieving GHG emission reduction targets given the use of ESPC by public agencies to reduce emissions from energy use in addition to the historical use of ESPC to to achieve cost/energy savings and ancillary benefits (e.g., addressing deferred maintenance, aging infrastructure, etc.). The analysis draws from LBNL’s eProject Builder (ePB) database, which contains approximately 3,000 energy retrofit projects implemented by energy service companies (ESCOs), mostly energy savings performance contract (ESPC) projects. This is the first report to model GHG emission reductions from ongoing ESPC projects in the U.S public sector based on ePB project data. It is intended for policymakers, federal, state and local government officials and other potential ESPC customers, the ESCO industry, researchers, and other energy policy professionals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1973

Studies in short haul air transportation in the California corridor: Effects of design runway length; community acceptance; impact of return on investment and fuel cost increases, volume 1

The impact of design runway length on the economics and traffic demand of a 1985 short haul air transportation system in the California Corridor was investigated. The community acceptance of new commercial airports for short haul service was studied. The following subjects were analyzed: (1) travel demand, (2) vehicle technology, (3) infrastructure, (4) systems analysis, and (5) effects on the community. The operation of the short haul system is compared with conventional airline operations.

Shevell, R. S.↗
NASA NTRS1978

Cargo Logistics Airlift Systems Study (CLASS). Volume 1: Analysis of current air cargo system

The material presented in this volume is classified into the following sections; (1) analysis of current routes; (2) air eligibility criteria; (3) current direct support infrastructure; (4) comparative mode analysis; (5) political and economic factors; and (6) future potential market areas. An effort was made to keep the observations and findings relating to the current systems as objective as possible in order not to bias the analysis of future air cargo operations reported in Volume 3 of the CLASS final report.

Burby, R. J.↗
NASA NTRSDate not supplied

Ocean and Earth System Modelling

Petascale supercomputing infrastructure + modelling and analysis capabilities + interdisciplinary upper-ocean expertise Multiscale ocean turbulence simulation Physical-biogeochemical interactions Analysis of large data sets from remote sensing and Earth system model ensembles

Ocean↗
DOE OSTI2024

Technical Assistance Opportunities for Tribes

The National Renewable Energy Laboratory (NREL) offers many forms of technical assistance for Tribes to support local clean energy priorities and challenges. With broad support from the U.S. Department of Energy (DOE) and local partners, NREL provides technical expertise to enable data-driven, informed clean energy decision making. Technical assistance may address energy strategy, project financing, policy design and development, data analysis, economic development, infrastructure planning, energy justice, climate change, resilience, or other energy priorities. NREL has a long history of partnering with Tribes and Tribal organizations, including in Alaska Native Villages where the extreme Arctic climate poses unique energy challenges. NREL works directly with Tribes to find solutions that address their self-defined energy priorities, challenges, and goals.

Alaska native village↗
DOE OSTI2024

Hydrogen Component Reliability Database (HyCReD)

The Hydrogen Component Reliability Database (HyCReD) is a collaborative project between the National Renewable Energy Laboratory, the University of Maryland, and hydrogen stakeholders to improve safety reliability for hydrogen facilities by integrating risk reduction methodologies and component reliability data taxonomies that support hydrogen infrastructure failure rate analysis.

availability↗
NASA NTRSDate not supplied

Tall Lunar Towers: Systems Analysis of a Lunar-Surface-Assembled Power, Communication, and Navigation Infrastructure

The National Aeronautics and Space Administration (NASA) intends to develop and maintain a human-lunar presence, requiring infrastructure on the Lunar South Pole. To keep pace with the continued growth in cislunar activity, there is national interest in developing a global lunar infrastructure network for power and Communication, Position, Navigation, and Timing (CPNT). Demonstrating autonomous construction capabilities is an infrastructure-enabling objective. This study explores several architecture trade studies to assess the feasibility of alternative lunar infrastructure concepts. 50 m towers, for instance, enable solar power generation up to 99% of a lunar year in addition to acting as wide-range communication and navigation surface relays. The infrastructure network considered in this study consisted of tower platforms, utilities hosted on the towers, and both crewed and robotic end users. High-level trades were analyzed, such as tower height, location, and distributed vs centralized power grids. Results indicated that even with minimal permanent surface assets (darkness survival power loads on the order of 5 kW or greater), at any of the five locations considered, taller towers resulted in lower infrastructure mass than shorter towers; up to 24% system mass savings were realized by reducing battery mass. Simultaneously, taller towers increased the range of communication coverage; a 50 m tower on the Connecting Ridge had 5 kg more structure and 76% more line-of-sight coverage to a two-meter-tall end user than a 10 m tower with the same location and user height. Leveraging a grid of tall towers for nominal power and communication would not only save up to 2,800 kg in battery mass but would be more maintainable and allow users to take advantage of generational upgrades.

lunar infrastructure↗
NASA NTRS2021

Characterization Study of TestBed Infrastructure Performance in a Distributed Simulation Environment: Baseline Analysis

Characterization of the performance of Air Traffic Management Exploration (ATM-X) TestBed integration environment has been investigated and documented for one system configuration for progressively increasing traffic. Several statistical parameters were used to assess the performance of the TestBed distributed system such as mean, standard deviation, skewness, and kurtosis of latency, and update rate for aircraft state messages that are transmitted through the simulated system under investigation. It is necessary to assess the performance characteristics of distributed systems in terms of the indicated statistical parameters mentioned above. It is critical to verify the system performance with respect to a researcher’s required system performance. Computer host specifications are documented in terms of Central Processing Unit (CPU) clock speed and core count. Transmission Control Protocol/ Internet Protocol (TCP/IP) message protocol was used for data transmission. The system network topology also contributes to the latency and update rate variations from the one imposed by the data source. The motivation for selecting the TestBed infrastructure as the focus of this study can be attributed to the number of services and capabilities it provides that help simplify the process of preparing and conducting a simulation. These capabilities include an easy to use GUI for simulation configuration, access to TestBed library by the end-user of other simulation software components, a modular adapter paradigm that allows simple connectivity of external software to TestBed, connectivity with other simulation laboratories, and a Software Development Kit (SDK) for quicker development. Two types of traffic generators, Air Traffic Generator (ATG) and Multi Aircraft Control System (MACS) were used to generate messages that were injected into the TestBed distributed environment. Eight different air traffic scenarios with progressively increasing loads were generated for each air traffic simulator. The corresponding air traffic loads between the two simulators had an identical number of aircraft per scenario, but different flight plans. It was observed that the performance of MACS degraded for air traffic scenarios containing more than 200 aircraft (37.5 KB/s nominal throughput). However, ATG performed adequately under all tested air traffic loads up to 1200 aircraft (225. KB/s nominal throughput). The tests show that MACS exhibits better latency performance with smaller aircraft loads when compared to ATG. The tests also show that the TestBed infrastructure successfully transmits 1200 aircraft without significant degradation of its performance. From the latency trends for both MACS and ATG, it is clear that as aircraft load increases, the latency in the system increases as well as its standard deviation. Likewise, the trends for the update data rate for both MACS and ATG show that as the aircraft load increases, so does the standard deviation and mean of the update rates which can be attributed to the performance of MACS and ATG applications. The analysis of the results of this study have proven that the overall system performance is dependent on the individual performance of each system component that is connected to TestBed, which subsequently propagates into the system. All TestBed characterization tests were conducted in SimLabs at NASA Ames Research Center in November 2019. This study addresses the need for a baseline TestBed characterization, and the results will serve as a reference for more complex simulation systems.

Air Traffic Management simulations↗
DOE OSTI2022

Macro Analysis to Estimate Electric Vehicles Fast-Charging Infrastructure Requirements in Small Urban Areas

Electric vehicles (EVs) are known to reduce emissions and fossil fuel dependency. However, the limited range, long charging time, and inadequate charging infrastructure have hampered the adoption of EVs. The current EV charging infrastructure planning studies and tools require detailed information, extensive resources, and skills that can be a significant barrier to urban areas for finding the required charging infrastructure to support a targeted EV market share. This study generates regression models to estimate the number of direct current fast charging stations and the chargers to support the EV charging demand for urban areas. These models provide macro-level estimates of the required infrastructure investment in urban areas, which can be easily implemented by policy-makers and city planners. This study incorporates data obtained from applying a disaggregate optimization-based charger placement model, developed recently by the same authors, for multiple case studies to generate the required data to calibrate the macro-level models, in the state of Michigan. This simulated data set includes the number of charging stations and chargers for each market share, technology advancement scenario, and the transportation network topology. The results show that the number of charging stations reduces with battery size and charging power and increases with EV market share and the road network lane length. The number of chargers reduces with charging power, whereas it increases with battery size, EV market share, and vehicle miles traveled in the system. The model developed here can be applied to any state having urban characteristics and weather conditions similar to Michigan.

Engineering↗
DOE OSTI2019

Co-Optimized Analysis and Design of Electric and Natural Gas Infrastructures

This paper proposes and implements a long-term deterministic capacity expansion model for the co-optimization of electric and natural gas infrastructures. It determines the required investments in generation units, transmission lines and pipelines for meeting future demands, while representing electricity and natural gas flows using DC Power Flow and Weymouth equations, respectively. A Mixed Integer Nonlinear Programming (MINLP) problem is developed, from which a linearized version is derived. A 26 node integrated gas-electric system for the Eastern Region of the United States is used to demonstrate the model’s capabilities. Results show that the model provides an accurate operational representation of the integrated system, and, therefore, enhances the expansion planning process.

47 OTHER INSTRUMENTATION↗