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NASA Initiatives to Support Renewable Energy and Sustainable Infrastructure

Initiatives to build and manage climate-resilient infrastructure require spatially explicit environmental and climate information. NASA’s vantage point of Earth from space provides valuable observations that, in concert with additional information, can be used to inform both the design and operation of infrastructure that builds resilience to climate stressors. In this presentation, we provide an overview of how NASA Earth science is used to support decision-making associated with climate adaptation and mitigation, with a particular focus on renewable energy and sustainable infrastructure. Much of this work is currently delivered through NASA’s Prediction of Worldwide Energy Resources (POWER) project, which generates high quality solar and meteorological data products that are customized to the needs of user communities. Importantly, these products are delivered through a variety of web-based applications that make it easier for users to access relevant and timely information. We will highlight several examples of how the impact of POWER is scaled via a robust user community and discuss further plans to expand impact. Additionally, this presentation will highlight efforts of the NASA Earth Science Division’s Energy & Infrastructure Applications program to expand collaborative activities with researchers and practitioners that work on renewable energy and sustainable infrastructure.

Allison K Leidner↗
DOE OSTI2024

Assessment of Alternative Fueling Infrastructure in the United States

NHTSA uses the Corporate Average Fuel Economy (CAFE) Model to analyze potential CAFE standards and their impact on emissions and vehicle fleet composition. The CAFE model analyzes the application of potential technologies to the current automotive industry vehicle fleet to determine the feasibility of future CAFE standards and the associated costs and benefits of the standards. A significant portion of the engineering input development is related to the effectiveness (energy consumption reduction) of each fuel-saving technology and the combination of several fuel-saving technologies, including AFVs. The purpose of this report is to deepen NHTSA's understanding of alternative fueling infrastructure and its potential impact on the adoption of alternative fuel vehicles (AFVs) so that AFVs can be more accurately and comprehensively incorporated into the CAFE Model. This report analyzes the current state of alternative fueling infrastructure in the United States and its relationship to the light-, medium-, and heavy-duty AFV markets; explores the costs associated with alternative fueling infrastructure; investigates trends driving the deployment of alternative fueling infrastructure; explores how the adoption of various vehicle and fuel technologies may look in the future; and analyzes the evolution of alternative fueling corridors.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. Further, the results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Estimating Fast Charging Infrastructure Requirements to Fully Electrify Ride-Hailing Fleets Across the United States

Ride-hailing electrification is made challenging by a variety of factors, including limited driver access to overnight charging and a nascent network of public direct-current fast charging (DCFC). This article projects the DCFC infrastructure needed to electrify ride-hailing across 384 cities in the United States. Research leveraging a novel infrastructure projection tool, Electric Vehicle Infrastructure Tool for On-Demand Mobility Services model (EVI-OnDemand), estimates that 25,400 DCFC ports capable of charging vehicles at a mean power of 150 kW are required to electrify 1.45 million ride-hailing vehicles in the baseline scenario. Results show that ride-hailing vehicles require 17.5 DCFC ports per 1000 vehicles, three times that of personal electric vehicles (EVs). Infrastructure demand is also shown to vary across cities; 63% more DCFC ports are needed to support 1000 battery EVs in Chicago versus Miami. The analysis also includes sensitivity studies that explore variation in charging demand across input assumptions, finding that charging power, vehicle class, overnight charging access rates, and port utilization influence the network size needed. Projections vary from 18,600 to 41,300 DCFC ports across sensitivity scenarios, indicating that ride-hailing electrification will require significant expansion of access to fast charging even in the most optimistic scenarios, and investments into supporting assets can reduce the scale of the public charging expansion needed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

2020 Transportation Research Board Workshop: Infrastructure Spatial Sensing at Intersections: The Potential to Enhance Safety and Enable Automation

The sensing technology that is enabling vehicle automation also can revolutionize traffic intersection safety, control, and efficiency. Infrastructure spatial sensing technology refers to the deployment of sensors that can detect and track all objects in the field of view - for example, mounting lidar sensors, radar, and video imaging at an intersection and fusing the data to produce a three-dimensional dynamic operational awareness. Combining such sensing capability with fail-safe vehicle communications can facilitate applications such as eco-approach and departure, optimizing efficient vehicle-signal coordination, and reducing traffic accidents through increasing safety. Furthermore, evidence is mounting suggesting that infrastructure-based sensing is needed in order to safely deploy automated public mobility alongside the normal vehicle and pedestrian traffic in our cities. Six speakers were invited to present their work from various aspects (safety, efficiency, and automation) addressing infrastructure-based sensing at the workshop on Infrastructure Spatial Sensing hosted in Washington DC as part of the Transportation Research Board Annual Meeting in January 12, 2019. A summary of the presentation are included herein.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Electrical Infrastructure Cost Model for Marine Energy Systems

The National Renewable Energy Laboratory's Electrical Infrastructure Cost Model is an Excel-based tool designed to estimate the electrical infrastructure costs of marine energy components and subsystems. It incorporates data collected from offshore wind projects, utility projects, and other relevant sources to provide accurate and comprehensive cost projections. With its user-friendly interface, the model allows users to input various parameters related to the system array, electrical cables, and substations. By leveraging industry data, cost trends, and technological advancements, the model generates outputs that include system array sizing, electrical cable specifications and costs, substation specifications and costs, and total electrical infrastructure costs. One of the notable strengths of the model is its flexibility in covering multiple-orders-of-magnitude scaled systems, accommodating projects ranging from proof-of-concept or pilot-scale installations to large-scale offshore systems. By collecting data largely from offshore wind reports and utility projects, the model incorporates real-world conditions and accounts for industry-specific factors. It incorporates cost trends and sizing relationships to deliver cost estimations for electrical infrastructure components, such as electrical cables and substation equipment.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Electric Medium- and Heavy-Duty Vehicle Charging Infrastructure Attributes and Development

Although more established for light-duty vehicles (LDVs), advancements in electric vehicle (EV) charging technology are being made in the medium- and heavy-duty (MD/HD) sector. Progress is also being made with the electrification of MD/HD vehicles, including transit buses, school buses, MD trucks, and HD trucks. The diverse set of operational requirements and duty cycles for each vocation, as well as the range in the size of fleets, present unique charging and infrastructure requirements. This report focuses on charging requirements for MD/HD vehicles and synergies with LDV infrastructure. This analysis leans toward the qualitative rather than quantitative because relevant model inputs are in development and will not be established for a few years, as EV deployments are more mature in the LDV sectors than MD/HD. The report begins with an overview of MD/HD vehicle classes and types of charging, including depot and residential charging, among others (Section 2). Section 3 analyzes the home bases (overnight dwell locations) of existing MD/HD vehicles, with an emphasis on depot and residential home bases, and discusses implications for charging infrastructure. Section 4 discusses the key characteristics for determining if, when, and where MD/HD vehicles can leverage LDV charging infrastructure rather than requiring dedicated chargers. These considerations include electricity demand, connectors, physical space requirements, payment considerations, and impacts on the grid. Section 5 summarizes shared characteristics for MD/HD vehicles that are appropriate for near-term electrification and includes a summary of the outlook of the electric MD/HD vehicle market. The conclusion (Section 6) summarizes the report's findings and outlines areas for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Evaluating Acoustic vs. AI-Based Satellite Leak Detection in Aging US Water Infrastructure: A Cost and Energy Savings Analysis

The aging water distribution system in the United States, constructed mainly during the 1970s with some pipes dating back 125 years, is experiencing significant deterioration leading to substantial water losses. Along with the potential for water loss savings, improvements in the distribution system by using leak detection technologies can create net energy and cost savings. In this work, a new framework has been presented to calculate the economic level of leakage within water supply and distribution systems for two primary leak detection technologies (acoustic vs. satellite). In this work, a new framework is presented to calculate the economic level of leakage (ELL) within water supply and distribution systems to support smart infrastructure in smart cities. A case study focused using water audit data from Atlanta, Georgia, compared the costs of two leak mitigation technologies: conventional acoustic leak detection and artificial intelligence–assisted satellite leak detection technology, which employs machine learning algorithms to identify potential leak signatures from satellite imagery. The ELL results revealed that conducting one survey would be optimum for an acoustic survey, whereas the method suggested that it would be expensive to utilize satellite-based leak detection technology. However, results for cumulative financial analysis over a 3-year period for both technologies revealed both to be economically favorable with conventional acoustic leak detection technology generating higher net economic benefits of USD 2.4 million, surpassing satellite detection by 50%. A broader national analysis was conducted to explore the potential benefits of US water infrastructure mirroring the exemplary conditions of Germany and The Netherlands. Achieving similar infrastructure leakage index (ILI) values could result in annual cost savings of $\$4$–$\$4.8$ billion and primary energy savings of 1.6–1.9 TWh. These results demonstrate the value of combining economic modeling with advanced leak detection technologies to support sustainable, cost-efficient water infrastructure strategies in urban environments, contributing to more sustainable smart living outcomes.

acoustic leak detection↗
NASA NTRS2023

Ground-Based Capabilities for Lunar Infrastructure Testing

A focus of NASA’s Moon-to-Mars objectives is the development of the infrastructure on the lunar surface that will be needed to support broader lunar surface operations. This infrastructure is intended to support both United States and international partners to expand human presence on the lunar surface. As this lunar infrastructure is designed and established, it will be critical to ensure that the various hardware elements work together to both enable the capabilities and to avoid unintended actions. NASA’s Glenn Research Center (GRC) is establishing ground-based testing and emulation facilities to mimic the lunar environment that the surface power and communications infrastructure will operate in. These facilities are intended to represent power and communications providers, users, and interfaces to ensure that systems operate as intended to support the lunar economy. They will empower industry to rapidly evaluate new technologies under realistic conditions. In 2023 GRC is opening a new, state-of-the-art, Aerospace Communications Facility featuring hardware-in-the-loop and ground-to-orbit testbeds. The Multiple Asset Testbed for Research in Innovative Communications Systems (MATRICS) capability will emulate the lunar communications environment, enabling validation of mission concepts and technologies to reduce risk through performance and operations testing, training, and uncover potential issues in compatibility among communication systems providers and users. In addition to the communications testbed, GRC is also developing a full-scale power grid to reduce lunar mission risk. The Adaptable Surface Power Integration and Research (ASPIRE) project aims to reduce mission and hardware risk via high-fidelity integrated testing and pave the way for commercially supplied utility power on the lunar surface. The facility will be scalable and highly adaptable and will be available to NASA, Industry, Academia, and International Partners. ASPIRE will allow developers to integrate and demonstrate their power solutions in a relevant environment, and it will be able to characterize the lunar power performance in representative mission contexts.

ground-based testing↗
DOE OSTI2023

Addressing Consequence within Operational Risk: An Approach for Understanding an Organization’s Unique Infrastructure Environment

The endeavor of tackling operational risk focused on consequences is challenging even for the most resourced entity but can be advanced though a simplified approach: identifying, binning, and prioritizing the infrastructure environment. While no two entities within a single element of the 16 critical infrastructure sectors are exactly alike when it comes to risk, there is a basic process to move toward a greater understanding of operational risk through becoming more informed about the infrastructure landscape in which the entity exists. The process starts with bringing internal and external stakeholders and subject matter experts together to analyze key areas such as Information Technology (IT) and Operational Technology (OT) components and points of convergence, analyzing internal and external cyber and physical dependencies, accounting for explosive growth in devices and wireless technology, and leveraging the contributions of people inside and outside the operational environment. Attaining a common understanding of the infrastructure landscape as part of addressing consequences within operational risk is not easy to do or resource light, but the process outlined provides the framework to further any entity’s efforts in this space.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Assessing Energy Infrastructure Devices for Vulnerabilities

Industrial control systems prove to be vital to the health and security of the nation in our critical infrastructure. Critical infrastructure includes the most foundational systems to support modern civilization which includes water and wastewater systems, communications, and the electricity we use to name a few sectors. However, these devices' overall composition remains largely unknown and are untested from a cyber security perspective. As part of the Cyber Testing for Resilient Industrial Control Systems (CyTRICS) program, I analyzed one such energy infrastructure device to better understand how it functions, what hardware and software components are present within it, and assess it for security vulnerabilities. To achieve this, I reverse engineered binary files using Ghidra to understand system functionality and learned more about how to collaborate with other researchers on a shared Ghidra project. I learned more about how web sockets function and how to interact with them through Python to test if they are secure or not. This work led me to assess possible vulnerabilities in this device and provide a better understanding of its composition and function, which are essential to INL's mission of securing our nation's energy infrastructure.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception

This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Safe Operations at Roadway Junctions: Intelligent Roadway Infrastructure as Functional Interlocking

Automated vehicle (AV) technology is quickly maturing, and the corresponding infrastructure systems that evaluate traffic and communicate to vehicles requires sophisticated sensing and perception technologies, referred to as intelligent roadway infrastructure (IRI), to complement emerging AV capabilities. IRI provides signals to vehicles, indicating right-of-way for vehicles and communicating to approaching AVs that no other vehicle is failing to yield. This capability, denoted as safety-affirmative signaling, provides a green light or a green arrow as appropriate and affirms through communication links to connected vehicles when it is safe to proceed. About 36% of collisions occur at intersections, with most occurring upon left turns (22.2%) or crossing over (12.6%), and only a small percentage (1.2%) while turning right at an intersection. Of all intersection crashes about half (52.5%) of those vehicles were traveling through a signalized intersection 2. Safety-affirmative signaling would guarantee safety of AV fleet vehicles, by providing the interlocking principle, a term from automated train control that only allows progression through a railway intersection after affirming no opportunity for a crash exists. IRI through safety-affirmative signaling would bring performance and safety to complex roadway intersections where AV transit fleet service is most needed, as well as safety benefits to traditional, non-automated vehicles and vulnerable road users. The implementation of IRI has functional, programmatic, and technical challenges. Research work performed at the National Renewable Energy Laboratory (NREL) in an integrative approach encapsulating these themes, and termed infrastructure perception and control (IPC) is motivated by improved performance (travel time), improved safety (reduced collisions), and improved energy efficiency (less fuel burned and minimized production of greenhouse gases). IPC is intended not only for roadway and intersection applications but also in extension to inform complementary buildings and grid systems to enable better co-management, as vehicles and their charging needs become increasingly integrated into the built environment. The NREL IPC project presents an open-source framework, architecture, and supporting technology to implement IRI, addressing critical issues such as fusion of data, reliability, standardization of data interfaces, and confidence of detection. The framework is informed by previous experience in U.S. Department of Defense research technology, specifically in the use of radar to detect, identify, and track aerial threats. These principles combined with multi-sensor fusion provides for a complete digital twin with known and measurable confidence and accuracy from which safety-affirmative signaling can be developed and deployed.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
DOE OSTI2022

Economic evaluation of infrastructures for thermochemical upcycling of post-consumer plastic waste

Thermochemical technologies, such as pyrolysis, offer a potentially scalable pathway for upcycling diverse types of plastic waste (PW) into value-added chemicals. However, deploying these technologies in waste management infrastructures is not straightforward because such systems involve a wide range of interdependent stakeholders, processing facilities, and products. In this work, we present a holistic optimization framework that integrates value-chain analysis, techno-economic analysis, and life-cycle analysis for investigating the economic viability and environmental benefits of upcycling infrastructures that collect, sort, clean, and process post-consumer PW for producing virgin polymer resins. The framework is applied to a case study in the upper Midwest region of the US. Our analysis reveals that the infrastructures are economically viable and could activate a regional circular economy that generates over 1 billion USD in annual profit. Moreover, our analysis reveals that this economy can reduce the carbon footprint of PW incineration by half. Our framework also determines the inherent values of post-consumer PW and of derived products such as plastic bales and pyrolysis oil; we find that, in these infrastructures, PW becomes a highly valuable feedstock with a market value of 500 USD per tonne. Here, we discuss how this market value can generate incentives that foster more effective waste pre-sorting practices by consumers that can help bypass material recycling facilities and increase total system profit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Data Processing Pipeline To Extract A Knowledge Graph From Sec Documents For Socio-technical Analysis Of Critical Infrastructure Influence

The code is written in Python and consists of the following pipeline that is implemented in Apache Airflow. This pipeline intends to understand the companies that are directly or indirectly involved with a type of critical infrastructure system at some point in that system's lifecycle. The pipeline takes a configuration file that specifies a list of initial companies to consider, a geographic region of interest (disk) expressed as a latitude/longitude point and distance, and a set of SEC form types from which to extract entities and relations. There are three main components to this pipeline as currently implemented: Social Network Extraction, Critical Infrastructure Network Extraction, and Inference and Fusion. First, Social Network Extraction, implemented as the `organizations_sec` component of the workflow graph queries the SEC EDGAR webservice using the list of initial companies from the configuration file. Given this, it extracts metadata that documents the number of each type of form for the given set of companies and their location. This forms metadata represents a catalog of data sources for the extracted social network knowledge graph. The pipeline then downloads these forms from the website and saves them in a build directory for further processing. These documents are then parsed for entities and relations. Second, the Critical Network Extraction component extracts entities and relations for a critical infrastructure sector. Currently, we focus on Electric Vehicle charging stations and this information is available via the Department of Energy (DOE) database on fueling stations maintained by NREL. Third, the Inference and Fusion component relates the social network graph to the critical infrastructure graph in order to understand the impact of a company within a geographic region. Relations include ownership of the EV Charging Station asset as well as maintenance/ownership of the EV payment networks. The fused network can be represented in many ways and currently we emit a knowledge graph.

Weaver, GabrielA.↗
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 OSTI2026

Model data for infrastructure-aware simulation of compound flooding at Alligator Bayou Watershed, southeast Texas

This dataset supports infrastructure-aware hydrologic modeling and flood scenario analysis for the Alligator Bayou Watershed, a highly managed urban watershed in Southeast Texas. It includes Jupyter notebooks for figure reproduction, model configuration files, simulation outputs, and derived products used to quantify the influence of engineered stormwater infrastructure on flood behavior across multiple spatial scales. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations on a channel-aligned mesh with explicit representations of pump stations, gate structures, detention basins, and impervious surfaces. Outputs include time series of gate and pump flows, stage observations, and water balance components, as well as spatially explicit fields of peak ponded depth and flood duration across multiple infrastructure scenarios spanning a single-location detention basin expansion, distributed drainage limitations, and compound coastal flooding. These data facilitate full reproducibility of the manuscript figures and support further research on urban flood dynamics and the role of stormwater infrastructure in shaping watershed-scale flood response.

EARTH SCIENCE > OCEANS > COASTAL PROCESSES↗
DOE OSTI2021

Infrastructure and Testing Needs for Molten Salt Reactor Safeguards

Molten salt reactors (MSRs) are an attractive advanced reactor technology because of their increased fuel utilization and efficiency, the ease of fueling, and the potential to use alternative fuel cycles, including thorium and breeder/burner scenarios. Since an MSR has never been domestically operated for commercial electricity production, minimal infrastructure exists to support performance and materials testing, reactor licensing (including research, test, and operating reactors), and technology development in general. These factors could present challenges for the commercialization of the proposed design technology. Several research and development efforts and investments have begun to identify and supplement the infrastructure to accommodate the molten salt concept, including the United States Department of Energy Office of Nuclear Energy Molten Salt Reactor Program. This report reviews safeguards technology and domestic infrastructure to support the evaluation of nuclear safeguards (primarily material control and accounting) measures and approaches for salt-fueled MSRs. Recommendations for potential priority infrastructure investments, including safeguards measurement test beds and future research, are presented.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗