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At least 55 records · Page 3

Calibration and Rapid-Adoption Forecasting Techniques

CRAFT (Calibration and Rapid-Adoption Forecasting Techniques) CRAFT is a Python-based project for processing, analyzing, and modeling atmospheric or environmental data. It uses machine learning techniques, specifically Random Forest Regression, to create emulators for various environmental variables such as gross primary production and soil water content. It then uses these emulators to robustly test the parameter space of mechanistic models to provide posterior estimations of the free parameters.

Robins, Zachary↗

Fighting the climate crisis with caloric heat pumping: Innovations to enable widespread adoption

Caloric heat pumping is a cross-cutting thermal energy technology that can cover a wide range of applications and temperatures, from millikelvins to hundreds of kelvins, with a working medium that has zero global warming potential. The technology promises cost savings and high efficiency, having 60% Carnot efficiency demonstrated to date. The Energy Earthshots™ Initiative, launched by the U.S. Department of Energy, aims to fight the climate crisis and overcome technological barriers to a decarbonized economy. The initiative focuses on the development of energy solutions that increase efficiency, reduce greenhouse gas emissions, and ensure affordability. Three out of eight Energy Earthshots™ look for alternative thermal energy technologies for extensive temperature ranges, from hydrogen liquefaction to metal-treating temperatures. Caloric heat pumping can fulfill all these requirements; however, at the current stage, caloric systems have limited presence in real-world applications. Further, this perspective discusses key efforts to address barriers hindering the widespread adoption of caloric technology. We focus on essential breakthroughs in and effective approaches to material discovery and draw a path to high-power-density, grid-interactive caloric systems to support achieving the ambitious net-zero carbon economy goal.

42 ENGINEERING↗

Accelerating the Adoption of the Solid Panel Structural System

This report, "Accelerating the Adoption of the Solid Panel Structural System", explores the structural properties, capabilities, and applications for an innovative “studless” building system that uses a plate-like approach and “Perfect Wall” principles for an efficient, durable, and robust wall system. A comprehensive testing regime was completed to fully characterize the structural behavior of the Solid Panel Structural system. These results were used to develop an engineering guide that can be used by architects and engineers for design and code approval.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

New Pathways for Equitable Solar Adoption in Texas

As part of the SEIN Round 3 program, a diverse group of energy stakeholders in Texas set out to develop and pilot new pathways to increase rooftop solar adoption at no upfront cost to lowincome households. One potentially promising pathway we identified involved combining funding from existing utility and federal programs promoting weatherization and energy efficiency. Our objective was to demonstrate pilot projects that equitably deployed rooftop solar to properties owned or rented by families in disadvantaged communities. Our goal was to create a clear path for lowincome households to achieve electricity bill relief and to access clean energy by leveraging existing utility energy efficiency programs with existing federal resources, such as the U.S. Department of Health and Human Services (HHS) Low-Income Home Energy Assistance Program (LIHEAP) and/or U.S. Department of Energy (DOE) Weatherization Assistance Program (WAP) funding in Texas. This has been attempted in a few other states with varying degrees of success, but not yet in Texas.

14 SOLAR ENERGY↗

Cyber-Informed Engineering Adoption in University Engineering Programs: An Overview of CIE Integration Successes at Nine U.S. Educational Institutions

This report examines the adoption of Cyber-Informed Engineering (CIE) in university engineering programs, driven by the need to protect critical energy infrastructure from adversarial threats. CIE equips current and future engineers and technicians with the necessary mindset, skills, and competencies to enhance the resilience of engineered systems against cyber attacks. This report highlights nine academic partners who are incorporating CIE into their curricula through various approaches, including lectures, courses, and certificates.

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Regulatory Sandboxes and Other Processes to Expedite Utility Adoption of Advanced Grid Technologies

Advanced grid technologies are increasingly important to enable electric transmission and distribution systems to meet growing demands. However, traditional regulatory processes typically lag technological advancements. Regulatory sandboxes, which provide a structured environment for testing new technologies and business approaches under modified rules to increase the speed of adoption, aim to bridge the gap between grid needs and opportunities to deliver solutions at scale. This report examines the role of regulatory sandboxes in promoting utility innovation, highlights examples of successful sandbox mechanisms, and provides emerging best practices for designing and implementing regulatory sandboxes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Addressing the Split Incentive Challenge for Enhanced Solar Adoption in Multifamily Rental Properties [Abstract]

The split incentive problem is particularly pronounced in rental markets, where landlords prioritize investments that directly increase property value or rental income. Since energy savings from solar photovoltaic (PV) systems primarily benefit tenants, landlords may perceive little return on investment unless mechanisms exist to recapture some of the financial gains. The primary objective of this project is to develop a publicly available, web-based tool to analyze the U.S. Department of Energy’s ResStock database, which models the U.S. residential building stock. The tool allows users to filter buildings by location, type, HVAC system, square footage, and other characteristics, and outputs typical electric load profiles. By leveraging location-specific electric load data, Fram Energy aims to advance business strategies that address the split incentive barrier and promote the adoption of solar PV installations in rental properties. In addition, a machine learning model will be developed to weigh the marginal contribution of building features across the dataset in predicting electricity demand, supporting guided decision making in forecasting electric load profiles. Lastly, based on each building’s location, load profile, and utility’s electricity rate, an optimized solar photovoltaic array and battery energy storage system will be sized to provide energy arbitrage opportunities.

14 SOLAR ENERGY↗

Regulatory and Technical Challenges and Barriers to Adoption of Distributed Wind Energy in Agricultural Settings

Distributed wind (DW) energy development can benefit agricultural landowners through the possibility of improved resilience of electrical service from onsite generation and associated economic benefits. DW development currently faces technical and regulatory challenges related to interconnection of projects with distribution or transmission equipment on the main electrical grid. A review was conducted of barriers to adoption for agricultural DW projects and potential roles of various stakeholders in addressing them. One major barrier is that the unique characteristics of wind energy generation such as its variability and intermittency, may require upgrades for the whole power line, which can lead to prohibitive cost burdens on individual interconnection customers. Another barrier is compliance with federal, state, or utility-level regulations that require technology-agnostic, industry-standard equipment that is often not technically realistic for DW projects. DW developers, grid infrastructure owner-operators, regulators, and standards publishers can work together to address these challenges and facilitate DW development.

17 WIND ENERGY↗

Advanced Data Center Energy Opportunities: Cloud and Infrastructure CoP - Data Center Energy and Efficiency with AI Adoption

The NLR portion of the "Cloud & Infrastructure CoP - Data Center Energy and Efficiency with AI Adoption" web meeting will cover data center locations, energy use and load growth, best practices, performance metrics, transition to direct liquid cooled data center equipment, and NLR's approach to optimizing data center.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ResStock Measure Documentation: Electric Vehicle Adoption With Level 1 Charging

This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 1 Charging" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ResStock Measure Documentation: Electric Vehicle Adoption With Level 2 Charging

This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ResStock Measure Documentation: Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility

This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ResStock Measure Documentation: Efficient Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility

This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Efficient Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

ResStock Measure Documentation: Efficient Electric Vehicle Adoption With Level 2 Charging

This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Efficient Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency

This work represents the largest and most comprehensive dataset to-date of responses surveyed from U.S. residents regarding home modifications and energy-related decision-making, including both objective measures describing the occupants and their homes and subjective measures describing the more unpredictable human factors behind residential decision-making. First, to develop the survey, we interviewed 121 individual decision-makers within their households regarding planned or completed projects. We used the insights of these interviews to design a survey that was distributed to 10,000 households across the U.S. The overarching topics approached in the survey include descriptive information about the respondent, their household, their home, home modifications they have made, and the human cognition-based contextual factors involved in home projects and decision-making, such as preferences, motivations, barriers, and information sources. The processed data from the survey was compiled into a dataset entitled UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency and represents the basis for the analyses included in this paper. The dataset represents a rich repository of home energy technology and modification decision-making results, the largest of its kind to-date. The abundance of contextual considerations within this dataset provides a robust resource for continual analysis, with possibilities for considering cross-cuts of data from a variety of perspectives.

Fuentes, Tracy L↗

From Resilient and Ready to Used and Useful: Managing Temporal and Locational Uncertainty in Electrification, DER Adoption, and Climate Adaptation

Grid planning decisions involve weighing risks against benefits. The best decisions will facilitate development of electrical infrastructure that minimizes risk and maximizes benefits. With the rapidly evolving energy landscape, today's planner must discern new loads and demand cycles; embrace the operational complexity of climate risk; revise settled standards; and anticipate and manage the system impacts of distributed energy resource (DER) adoption. Only by managing the combined uncertainty of these dynamic processes can a planner hope to make effective decisions. Our analysis focuses on the management of temporal and locational uncertainty, and particularly on the risks presented to customers by the mismanagement of the factors that are the sources of these uncertainties.

climate↗

Enabling the broader adoption of fusion simulation on complex geometry

This project addressed a key barrier to advanced fusion and nuclear simulation: the difficulty of performing high-fidelity Monte Carlo neutronics directly on complex, real-world CAD geometry. Traditional workflows require engineers to rebuild CAD models as simplified constructive solid geometry, a time-consuming and error-prone process that limits design iteration and broader adoption of simulation tools. The goal of this Phase I SBIR was to make CAD-based neutronics practical, accessible, and robust for industrial and research users. During the project, Coreform significantly enhanced the Direct Accelerated Geometry Monte Carlo (DAGMC) workflow and fully integrated it into Coreform Cubit as a first-class capability. Major achievements include optimized material assignment and surface meshing workflows, substantial performance improvements to geometry imprinting and preparation, native export of DAGMC models, and new visualization tools to support OpenMC source definition and lost-particle debugging. Coreform also expanded Cubit’s capabilities as a full OpenMC preprocessor, including the ability to convert OpenMC constructive solid geometry models back into CAD for visualization, multiphysics coupling, and debugging. In collaboration with Argonne National Laboratory, the project delivered comprehensive new DAGMC documentation and training materials, transforming DAGMC from a research-oriented tool into a production-ready workflow. Results were disseminated through tutorials, conference training, and multiple well-attended webinars demonstrating integrated CAD-based neutronics and multiphysics workflows. Overall, this project demonstrated that high-fidelity Monte Carlo simulations can be performed directly on complex CAD geometry, reducing setup time, improving usability, and enabling faster, more informed design decisions for fusion and nuclear energy systems.

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