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All sources NASA NTRS DOE OSTI

DOE OSTI2022

PV Hosting Capacity Estimation: Experiences with Scalable Framework

Hosting capacity is an indication of the amount of solar photovoltaics (PV) that can be hosted in a distribution system without additional changes to infrastructure or oper-ations. This paper presents a framework for estimating the PV hosting capacity at scale. First, we analyze computational, modeling and other key challenges of performing relevant, large-scale simulations, provided along with the experiences and lessons learned. Then, we develop two open-source Python-based software tools to conduct repeatable distribution analyses: the Distribution Integration Solution Cost Options (DISCO) for configuring and analyzing simulations and the Job Automation and Deployment Engine (JADE) for parallelizing jobs on high-performance computing clusters. A case study of hosting capacity estimation for the SMART-DS San Francisco (SFO) 2000+ synthetic feeders, is used to demonstrate the capability of the developed DISCO+JADE framework and tools. The framework and tools can help utilities assess the overall hosting capacity of their service territory, which can help them better plan for the overall upgrade costs to integrate more PV in the future. The experiences are shared to aid the tool users and researchers to conduct relevant studies and research.

distributed energy resources↗

NASA NTRS2002

Flight Evaluation of the Army/NASA Variable Stability Fly-by-Wire Rotorcraft Aircrew Systems Concept Airborne Laboratory (RASCAL) JUH-60A

NASA Ames Research Center and the U.S. Army Aeroflight dynamics Directorate (AFDD) have performed initial flight evaluations of the Research Flight Control System (RFCS) integrated into the Army/NASA Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-GOA. The highly modified JUH-GOA Black Hawk helicopter is a full authority, high bandwidth, variable stability, in-flight simulator designed to support development of advanced flight control, sensor, and integrated display and control technologies in a fail safe environment. Preparation for flight test required an extensive hazard analysis and ground testing to ensure proper system operation. A hardware in the loop development facility was utilized to evaluate control law stability following software changes, assess servo hardover upset conditions during manual and monitor disengagements and provide pilot familiarization of test techniques and software changes prior to flight. First engagement of the RFCS was conducted on 31 Aug 2001. RFCS transfer system operation, envelope expansion and a limited rate monitor evaluation have been completed with low bandwidth and model following control laws. The presentation will discuss the following - System overview including aircraft modifications and integrated development facilities used with the RASCAL facility. - Preliminary hazard identification and mitigation prior to flight test. - Ground testing used to qualify the RFCS transfer system and verify fault monitor operation. - Flight test results of low-bandwidth and model following control law evaluations including maneuver agility, control limitations, fault monitor reliability, and recovery from manual and monitor disengagement. - Lessons learned including test techniques using a passive three-axis sidearm controller, the value of the development facility in reducing risk and crew coordination issues related to the operation of a full authority, variable stability platform. - Future research and modifications planned for the RASCAL aircraft.

Dave Arterburn↗

NASA NTRS2015

T-38 Primary Flight Display Prototyping and HIVE Support Abstract & Summary

This fall I worked in EV3 within NASA's Johnson Space Center in The HIVE (Human Integrated Vehicles & Environments). The HIVE is responsible for human in the loop testing, getting new technologies in front of astronauts, operators, and users early in the development cycle to make the interfaces more human friendly. Some projects the HIVE is working on includes user interfaces for future spacecraft, wearables to alert astronauts about important information, and test beds to simulate mock missions. During my internship I created a prototype for T-38 aircraft displays using LabVIEW, learned how to use microcontrollers, and helped out with other small tasks in the HIVE. The purpose of developing a prototype for T-38 Displays in LabVIEW is to analyze functions of the display such as navigation in a cost and time effective manner. The LabVIEW prototypes allow Ellington Field AOD to easily make adjustments to the display before hardcoding the final product. LabVIEW was used to create a user interface for simulation almost identical to the real aircraft display. Goals to begin the T-38 PFD (Primary Flight Display) prototype included creating a T-38 PFD hardware display in a software environment, designing navigation for the menu's, incorporating vertical and horizontal navigation bars, and to add a heading bug for compass controls connected to the HSI (Horizontal Situation Indicator). To get started with the project, measurements of the entire display were taken. This enabled an accurate model of the hardware display to be created. Navigation of menu's required some exploration of different buttons on the display. The T-38 simulator and aircraft were used for examining the display. After one piece of the prototype was finished, another trip of to the simulator took place. This was done until all goals for the prototype were complete. Some possible integration ideas for displays in the near future are autopilot selection, touch screen displays, and crew member preferences. Complete navigation, control, and function customization will be achievable once a display is fully developed. Other than the T-38 prototyping, I spent time learning how to design small circuits and write code for them to function. This was done by adding electronic circuit components to breadboard and microcontroller then writing code to speak to those components through the microcontroller. I went through an Arduino starter kit to build circuits and code software that allowed the hardware to act. This work was planned to assist in a lighting project this fall but another solution was discovered for the lighting project. Other tasks that I assisted with, included hands on work such as mock-up construction/removal, logic analyzer repairs, and soldering with circuits. The unique opportunity to be involved work with NASA has significantly changed my educational and career goals. This opportunity has only opened the door to my career with engineering. I have learned over the span of this internship that I am fascinated by the type of work that NASA does. My desire to work in the aerospace industry has increased immensely. I hope to return to NASA to be more involved in the advancement of science, engineering, and spaceflight. My interests for my future education and career lie in NASA’s work - pioneering the future in space exploration, scientific discovery and aeronautics research.

Boniface, Andrew↗

DOE OSTI2023

Predicting future well performance for environmental remediation design using deep learning

Here in this study, we developed a deep learning (DL) framework with a multi-channel three-dimensional convolutional neural network (MC3D-CNN) to predict well performance and thereby assist future environmental remediation design. Such prediction of extraction well performance at designated locations is critical for configuring pump-and-treat (P&T) well network design and operation, setting reasonable target closure dates for overall remedying, and estimating remedy costs. The framework is developed with operational and monitoring data routinely collected during P&T remedy operations, including well extraction and injection rates as well as in situ contaminant concentrations. Traditionally, the collected data were rarely used for purposes other than assessing past well performance and the accuracy of the conceptual site model. However, recent advances in data-driven computational approaches enable better use of the large datasets to inform future well performance, enhance site characterization, and improve remediation planning. In this study, we established a DL framework to integrate transient three-dimensional contaminant plumes and multiple aquifer properties (e.g., hydraulic conductivity and hydrostratigraphic maps) to identify characteristic patterns controlling and representing extraction well mass recovery, aiming at providing future mass recovery estimates for existing wells and candidate wells at any proposed locations. We evaluated our framework by using a realistic synthetic dataset generated from a well-calibrated flow and transport model used in the 200 West Area of the U.S. Department of Energy’s Hanford Site in southeastern Washington state. The multi-channel feature in our framework allows integration of various types and temporal densities of training datasets for DL model development. Overall, we found that the trained DL model achieved an accuracy of over 90% in ranking extraction well performance in validation datasets, and over 80% in predicting high-performance-ranking well locations. This data-informed approach provides a flexible tool to support adaptive site management, streamline decision-making, and potentially reduce remediation time and costs. Our DL framework can be used as a filtering tool to improve the current P&T network optimization design by reducing the number of candidate well locations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Managing Traffic on the Three-Way Street: Steps Toward Closing the Aerosol Forcing Uncertainty Gap

Understanding changes in the radiative forcing of climate is critical for any effort to attribute, mitigate, or predict climate change. Although greenhouse gases (GHGs) contribute most of the radiative forcing, uncertainty in the climate forcing by airborne particles (aerosols) dominates the uncertainty in forcing changes overall. Yet, aerosol forcing has remained virtually undiminished for more than 20 years despite considerable advances in most of the key contributing elements. Satellite and suborbital measurements, as well as modeling, each have essential roles to play in reducing the uncertainty in the aerosol forcing of climate. This presentation will begin by briefly covering the reasons why aerosols are important for climate study, and will then summarize what we are learning about aerosols from current satellite remote-sensing work, and allude to the roles of suborbital measurements and models. Emphasis will be placed on nascent efforts to link satellite data with models, the need to continue as planned current programs supporting advanced, global-scale satellite and surface-based aerosol and precursor gas observations, climate modeling, as well as intensive field campaigns aimed at characterizing the underlying physical and chemical processes involved. The talk will conclude by highlighting new efforts needed to obtain systematic in situ measurements of aerosol microphysical and chemical properties, along with a greater research focus on integrating the unique contributions of measurements and modeling toward reducing the aerosol climate forcing uncertainty gap.

aerosol↗

NASA NTRS2016

Human Factors Checklist: Think Human Factors - Focus on the People

A quick-look Human Factors (HF) Checklist condenses industry and NASA Agency standards consisting of thousands of requirements into 14 main categories. With support from contractor HF and Safety Practitioners, NASA developed a means to share key HF messages with Design, Engineering, Safety, Project Management, and others. It is often difficult to complete timely assessments due to the large volume of HF information. The HF Checklist evolved over time into a simple way to consider the most important concepts. A wide audience can apply the checklist early in design or through planning phases, even before hardware or processes are finalized or implemented. The checklist is a good place to start to supplement formal HF evaluation. The HF Checklist was based on many Space Shuttle processing experiences and lessons learned. It is now being applied to ground processing of new space vehicles and adjusted for new facilities and systems.

Human Factors; Human Systems Integration↗

DOE OSTI2024

Leverage modern artificial intelligence (AI) enabled systems for waste reduction

Manufacturing industries continue to face challenges in reducing waste, as upstream strategies such as source reduction and product redesign require a deeper understanding of processes compared to conventional recycling methods. Recent advancements in artificial intelligence (AI) and machine learning (ML) have opened new opportunities to integrate modern computational techniques with traditional waste minimization strategies. This paper explores AI-enabled approaches for product redesign, source reduction, and recycling that can significantly reduce waste generation while improving efficiency and sustainability. AI-driven material substitution and lightweighting in product design enable discovery of novel materials with optimized properties, reducing waste without compromising performance. Reinforcement learning models optimize process parameters, raw material specifications, and machine sequencing to minimize production losses, while Industrial Internet of Things (IIoT) systems paired with AI analytics enhance real-time waste tracking, predictive maintenance, and quality inspection. Furthermore, AI-based demand forecasting and production planning reduce overproduction and excess inventory, as demonstrated in industrial applications. In recycling, ML-powered pattern recognition and robotic sorting technologies achieve higher accuracy in waste segregation, directly improving recycling efficiency. Complementary solutions such as smart bins and AI-enabled waste pickup scheduling optimize collection logistics, reducing both costs and emissions. Although implementation requires upfront investment in infrastructure and training, the long-term benefits include higher material efficiency, reduced waste, improved product quality, and stronger sustainability outcomes across the supply chain. By leveraging AI-enabled systems, manufacturers can align waste minimization efforts with circular economy principles, creating scalable solutions for both industry and society.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Synopsis of NREL's Automated Mobility District (AMD) Research Program and Associated Publications

An automated mobility district (AMD) envisions a system of integrated mobility options that serves major activity centers such as campuses, central business districts, and large medical facilities. The National Renewable Energy Laboratory (NREL) has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings. This document provides a synopsis of findings revealed over the last three phases of work, which have yielded insights into the creation and management of AMDs anticipated to use automated vehicle (AV) technology over the next decade. Phase I and Phase II tracked the deployment and lessons learned from 10 early-stage demonstrations of automated shuttle deployments, and their associated insights into the challenges for automated driving systems to achieve safe operations within district-scale deployments. Phase III began in-depth investigations of critical subsystem components, as automation, electrification, and on-demand service continue to converge within initial AMD operations. These directed studies focus on elements of electrification, curbfront/station management, the role of infrastructure sensing, and overall integration of AMD safety management in central, simultaneous coordination of multiple AMD fleets. Future research in AMDs includes systems engineering methodology (more frequently referred to as "digital twins") for planning, design, testing, and ongoing operation of AMDs; location (or co-location) of management functions; and human supervision and passenger communications for safety and security in unattended vehicles. The synopsis references the foundational research products (papers and presentations) that have been published through conference proceedings, journal articles, and NREL reports.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2010

Overview of NASA's Thermal Control Technology Development Project

NASA?s Constellation Program included the Orion, Altair, and Lunar Surface Systems project offices. The first two elements, Orion and Altair, were planned to be manned space vehicles while the third element was much broader and included several sub-elements including Rovers and a Lunar Habitat. The planned missions involving these systems and vehicles included several risks and design challenges. Due to the unique thermal operating environment, many of these risks and challenges were associated with the vehicles? thermal control system. NASA?s Exploration Technology Development Program (ETDP) consisted of several technology development projects. The project chartered with mitigating the aforementioned thermal risks and design challenges was the Thermal Control System Development for Exploration Project. These risks and design challenges were being addressed through a rigorous technology development process that was planned to culminate with an integrated thermal control system test. Although these Constellation elements have been cancelled or significantly changed, the thermal technology development process is being continued within a new program entitled Enabling Technology Development and Demonstration (ETDD). The current paper summarizes the development efforts being performed by the technology development project. The development efforts involve heat acquisition and heat rejection hardware including radiators, heat exchangers, and evaporators. The project has also been developing advanced phase change material heat sinks and performing a material compatibility assessment for a promising thermal control system working fluid. The to-date progress and lessons-learned from these development efforts will be discussed throughout the paper.

Stephan, Ryan A.↗

DOE OSTI2021

State Insights On The Water-Energy Nexus And Policy Ideas To Achieve Greater Savings

Governors, state policymakers, utilities and other stakeholders across the country are increasingly aware of the connection between energy and water production and use, and the need to conserve both resources to meet economic and environmental goals. It requires substantial amounts of water to produce energy and considerable amounts of energy to treat and deliver water. The critical interdependence between energy and water was clearly illustrated during the recent winter storm in Texas and other parts of the South in February 2021. Initial power outages contributed to a longer-term water crisis. Power outages led to water pump failures while water demand increased from frozen water pipes that burst. This caused low water pressure that can lead to harmful bacteria growth in the water. The power outages also prevented water treatment plants from properly treating the water for several days, thereby leaving many residents without clean drinking water and worsening the storm’s impacts. The National Governors Association has been working with states on this connection between water and energy and strategies for conserving those resources for several years. NGA held a Water-Energy Nexus Learning Lab in September 2020. This event invited two leading states in the water-energy nexus space, Arizona and Wisconsin, to showcase some of their model policies and programs to other states, Maryland, Nevada, North Carolina, North Dakota, and Washington, looking for greater savings opportunities. This paper provides an overview of challenges that states are facing in developing integrated water and energy conservation policies; provides background on Arizona and Wisconsin’s innovative water-energy policies and programs; and summarizes action items the participating state teams identified for their respective states. The main categories of policy solutions identified by states at NGA’s Water-Energy Nexus Learning Lab were: Funding & Financing – providing financial incentives for water efficiency modeled after established energy efficiency programs, and an emphasis on financial support for small water and energy utilities. Education & Technical Assistance – providing more education and training opportunities about ways to achieve cost-effective energy and water savings, and the needs of resource-constrained small and medium utilities for training and other assistance. Structural Changes to Encourage Conservation – developing ways to incentivize agricultural conservation such as through water allocation strategies; adopting water reuse or water loss standards; and requiring electric utilities to consider water impacts as part of their integrated resource planning process. Communications & Data – conducting energy audits, reviewing water data provided to state agencies, and developing data benchmarking tools to measure and better manage energy and water use. Climate Strategy – establishing a multi-agency working group or other collaborative approach to determine ways to integrate energy and water savings in state policies and help meet the state climate objectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2023

Addressing Regulatory Burdens to Accessing Solar Among Municipal, Commercial and Institutional Customers Through Collaborative Partnerships (Final Technical Report)

The project focused on providing education to large energy customers, with a focus on local governments, to help them better understand and overcome barriers to solar energy adoption that currently exist (or could exist) in utility planning processes and/or within wholesale energy markets. The project team created accessible educational materials — ranging from reports to case studies to webinars — that could connect with stakeholders who rarely engage in these venues, have limited bandwidth to do so, and possess little previous knowledge of these issues. The project team focused on sharing lessons learned and best practices based on the experiences of other local governments and large energy users that have engaged on these issues, including the PJM Cities and Communities Coalition (PJMCCC). The project sought to better connect these customers and other stakeholders to deepen and expand opportunities for them to engage together on these issues, as well as build peer networks to facilitate the exchange of information. The project team held convenings of key partners — such as local governments, developers, regulators, utilities and large solar buyers — to discuss best practices, develop research products to broaden stakeholders’ knowledge base, and to foster these peer networks.

14 SOLAR ENERGY↗

NASA NTRSDate not supplied

Lessons Learned From Designing and Building Low Organic Outgassing Cleanrooms for NASA OSIRIS-REx and Hayabusa2 Curation Facility

NASA Johnson Space Center Astromaterials Acquisition and Curation Office completed construction and commissioning of the OSIRIS-REx and Hayabusa2 cleanroom laboratory suites along with new precision cleaning and advanced curation laboratories consisting of ISO Class 5, 6, and 7 cleanrooms. The new curation facilities are designed for initial receiving, basic characterization, curation processing, and preliminary examination of carbonaceous asteroidal material. The facilities are also designed to enable long-term pristine sample storage to preserve the scientific integrity of each sample to enable future research by the international science community. The scientific study of organics is critical for both missions. The OSIRIS-REx mission instituted a stringent contamination control plan for low organics. Given these mission requirements and long-term storage preservation requirements, cleanroom construction materials were carefully selected to not hinder the scientific search for amino acids and the study of organics in the samples. Cleanroom candidate construction materials were researched for the HVAC system, floors, walls, ceiling, and plenum areas. The team chose several candidate materials that were further tested for their specific outgassing characteristics using ASTM E-595 per ASTM E-2312. The information gained provided the foundation for the final design selection of the cleanroom materials. While material selection is important before and during the facility design phase, the construction phase is where these choices are implemented by the prime construction contractor through final product and material submittals. These submittals are the last check point and changes are often submitted due to engineering/construction conflicts, especially when renovating an existing building. Any new material or equipment/product change must be identified and scrutinized for low particulate shedding and outgassing properties. In some cases, quick testing of new material is required, and compromises must be made in real-time. Careful selection and implementation of cleanroom materials significantly reduced organic and inorganic contamination beyond normal cleanroom baselines.

astromaterials curation↗

NASA NTRSDate not supplied

Lessons Learned From Designing and Building Low Organic Outgassing Cleanrooms for NASA OSIRIS-REx and Hayabusa2 Curation Facility

astromaterials curation↗

NASA NTRS2006

NASA Crew and Cargo Launch Vehicle Development Approach Builds on Lessons from Past and Present Missions

The United States (US) Vision for Space Exploration, announced in January 2004, outlines the National Aeronautics and Space Administration's (NASA) strategic goals and objectives, including retiring the Space Shuttle and replacing it with new space transportation systems for missions to the Moon, Mars, and beyond. The Crew Exploration Vehicle (CEV) that the new human-rated Crew Launch Vehicle (CLV) lofts into space early next decade will initially ferry astronauts to the International Space Station (ISS) Toward the end of the next decade, a heavy-lift Cargo Launch Vehicle (CaLV) will deliver the Earth Departure Stage (EDS) carrying the Lunar Surface Access Module (LSAM) to low-Earth orbit (LEO), where it will rendezvous with the CEV launched on the CLV and return astronauts to the Moon for the first time in over 30 years. This paper outlines how NASA is building these new space transportation systems on a foundation of legacy technical and management knowledge, using extensive experience gained from past and ongoing launch vehicle programs to maximize its design and development approach, with the objective of reducing total life cycle costs through operational efficiencies such as hardware commonality. For example, the CLV in-line configuration is composed of a 5-segment Reusable Solid Rocket Booster (RSRB), which is an upgrade of the current Space Shuttle 4- segment RSRB, and a new upper stage powered by the liquid oxygen/liquid hydrogen (LOX/LH2) J-2X engine, which is an evolution of the J-2 engine that powered the Apollo Program s Saturn V second and third stages in the 1960s and 1970s. The CaLV configuration consists of a propulsion system composed of two 5-segment RSRBs and a 33- foot core stage that will provide the LOX/LED needed for five commercially available RS-68 main engines. The J-2X also will power the EDS. The Exploration Launch Projects, managed by the Exploration Launch Office located at NASA's Marshall Space Flight Center, is leading the design, development, testing, and operations planning for these new space transportation systems. Utilizing a foundation of heritage hardware and management lessons learned mitigates both technical and programmatic risk. Project engineers and managers work closely with the Space Shuttle Program to transition hardware, infrastructure, and workforce assets to the new launch systems, leveraging a wealth of knowledge from Shuffle operations. In addition, NASA and its industry partners have tapped into valuable Apollo databases and are applying corporate wisdom conveyed firsthand by Apollo-era veterans of America s original Moon missions. Learning from its successes and failures, NASA employs rigorous systems engineering and systems management processes and principles in a disciplined, integrated fashion to further improve the probability of mission success.

Dumbacher, Daniel L.↗

NASA NTRS2013

Moving Technologies from the Test Tube to Commercial Products

Successful technologies include objects, processes, and procedures that share a common theme; they are being used to generate new products that create economic growth. The foundation is the invention, but the invention is a small part of the overall effort. The pathway to success is understanding the competition, proper planning, record keeping, integrating a supply chain, understanding actual costs, intellectual property (IP), benchmarking, and timing. Additionally, there are obstacles that include financing, what to make, buy, and sell, and the division of labor i.e. recognizing who is best at what task. Over the past two decades, NASA Langley Research Center (LaRC) has developed several commercially available technologies. The approach to commercialization of three of these inventions; Langley Research Center-Soluble Imide (LaRC-SI, Imitec Inc.), the Thin Layer Unimorph Driver (THUNDER, FACE International), and the Macrofiber Composite (MFC, Smart Material Corp.) will be described, as well as some of the lessons learned from the process. What makes these three inventions interesting is that one was created in the laboratory; another was built using the previous invention as part of its process, and the last one was created by packaging commercial-off-the-shelf (COTS) materials thereby creating a new component.

Bryant, Robert G.↗

NASA NTRS2021

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.

Advanced avionics↗

DOE OSTI2023

Beyond Price Taker: Conceptual Design and Optimization of Integrated Energy Systems Using Machine Learning Market Surrogates

Future electricity generation systems must be optimized to provide flexibility that counteracts the variability of non-dispatchable renewable energy sources and ensures the reliability and safety of critical infrastructure, including the electric grid. The current state-of-the-art is to co-optimize the design and operation of integrated energy systems (IES) treating historical or predicted time-series electricity prices as fixed parameters. Recent literature has shown the limitations of this price taker assumption, which neglects how IES optimization decisions influence market outcomes. As such, this paper proposes a new optimization formulation that uses machine learning surrogate models, trained from a library of annual market operation simulations, to embed IES market interactions into the co-optimization problem directly. Using a thermal generator example built in the open-source IDAES computational environment, we show that the price taker approach routinely over-predicts annual revenues by 8% or more compared to a validation simulation, where the proposed approach has a typical relative error of 1% or less.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

AI-Driven Frameworks for Characterizing Urban Energy Systems

We develop AI-driven frameworks to characterize urban energy systems with the goal of transforming planning by reducing the labor of model generation, scaling scenario exploration, and improving accuracy for localized analysis. The approach integrates top-down and bottom-up data to train different AI models that predict missing information and generate inputs and targeted scenarios for district-scale models. The result is a scalable framework that provides actionable insights for reliable and efficient planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗