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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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At least 253 records · Page 14

The DREAM approach to demand-side emissions reductions in Indonesia, 2020–2060

Indonesia’s current energy system modeling is heavily focused on the supply side, but emissions reductions in the demand sector have a significant impact on advancing Indonesia’s ambitious emissions reductions goals. To address the gap, we develop a new modeling tool DREAM Indonesia based on a bottom-up, technology-rich demand side framework and formulate projections of demand-side emissions reductions in Indonesia in 2020–2060. We find that demand-side energy efficiency and electrification can halve the growth rate of final energy demand to 1.4% annually over 2020–2060 and reverse the growing trend of emissions. The feasibility of full electrification by 2060, coupled with rapid adoption of existing technologies, positions the building sector as a model for achievable decarbonization and a cornerstone of Indonesia’s emissions reductions ambitions. In the industrial sector, extensive emissions reductions of 87% by 2060 (compared to business-as-usual) are achievable through energy efficiency improvements, alongside enhanced material efficiency measures including optimized material usage, low-carbon substitutions, innovative technologies, and increased circularity. In the transportation sector, balancing final energy demand by incorporating energy efficiency improvements across all transport modes, along with electrification particularly in road transportation, could decrease the emissions by up to 82% in 2060 compared to business-as-usual. This study provides insights and modeling approaches for rapidly growing Asian economies as well as other developing countries facing combined development and decarbonization challenges.

DREAM Indonesia↗

Machine Learning Enabled Sensor Fusion for In-Situ Defect Detection in Laser Powder Bed Fusion

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. The current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques such as X-Ray Computed Tomography (XCT), which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. RTX Technologies Research Center (RTRC) has licensed ORNL’s Peregrine software package – a printer- and camera-agnostic data analytics tool designed specifically for detecting process anomalies using in situ data collected during powder bed printing. The goal of this project was to feed temporally rich, multi-modal sensor data, including visible light, integrated near infrared (NIR), and spatially mapped co-axial melt pool thermal emission data into Peregrine to enable detection of subsurface flaws. XCT data was used as ground truth training data to allow Peregrine’s deep learning algorithms to recognize anomalies in these complex data streams in both test artifacts and industrially relevant geometries. Completion of this program has seen the successful implementation of multi-modal, multi-layer sensor data footprints for training of machine learning models in Peregrine. Flaws detected in XCT data have been successfully detected directly from this in situ data footprint, and initial analyses of the in situ probability-of-detection has been conducted, showing performance levels commensurate with traditional non-destructive evaluation (NDE) methods. The in situ monitoring methodology was then applied to an industrially relevant component that was using post-build NDE, highlighting the utility of the proposed method for hard-to-inspect AM components. As a direct result of this program, two journal manuscripts [1], [2] have been published in Additive Manufacturing, with additional manuscripts planned following program completion.

36 MATERIALS SCIENCE↗

Life Cycle Inventory Availability: Status and Prospects for Leveraging New Technologies

The demand for life cycle assessments (LCA) is growing rapidly, which leads to an increasing demand of life cycle inventory (LCI) data. While the LCA community has made significant progress in developing LCI databases for diverse applications, challenges still need to be addressed. This perspective summarizes the current data gaps, transparency, and uncertainty aspects of existing LCI databases. Additionally, we survey and discuss novel techniques for LCI data generation, dissemination, and validation. We propose key future directions for LCI development efforts to address these challenges, including leveraging scientific and technical advances such as the Internet of Things (IoT), machine learning, and blockchain/cloud platforms. Adopting these advanced technologies can significantly improve the quality and accessibility of LCI data, thereby facilitating more accurate and reliable LCA studies.

blockchain platforms↗

Promoting regulatory acceptance of combined ion and neutron irradiation testing of nuclear reactor materials: Modeling and software considerations

As the needs for the nuclear energy industry continue to evolve in the 21st century, timely adoption of new technological solutions acceptable to regulatory agencies is critical. Quantitative prediction of radiation damage in materials and its impact on mechanical properties is a key component of licensing and regulatory decisions regarding nuclear power plants. Accelerated testing methodologies such as combined ion and neutron irradiation data sets are crucial for the development and deployment of new materials and new manufacturing methods (e.g., additive manufacturing). However, regulatory acceptance of accelerated testing methodologies is necessary for their adoption. Further, the present work discusses the fundamental basis for comparing ion- and neutron-induced material microstructures, the theory behind interpreting radiation damage across length and time scales and radiation types, and the codes, standards, and quality assurance concerns surrounding different modeling methods and software. In particular, recommendations are given as to the path forward that will enable national laboratories, academia, and industry to develop the modeling and software basis for regulatory acceptance of the combined use of ion and neutron irradiation for material performance evaluation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Bridging the Energy Future: The Role and Potential of Hydrogen Co-Firing with Natural Gas

In the transition toward sustainable energy systems, the co-firing of hydrogen (H2) with natural gas emerges as a critical technology for cleaner power generation. This study examines its benefits, including emissions reduction, enhanced efficiency, and compatibility with existing infrastructure. Concurrently, it addresses the inherent challenges, such as combustion dynamics, necessary infrastructure modifications, and economic considerations. Incorporating global case studies, the review explores recent advancements in hydrogen production and co-firing, evaluating their practicality and operational efficiency. It also provides a critical examination of the economic implications and societal acceptance, which are crucial for the adoption of hydrogen technologies. Moreover, the review investigates the synergy between hydrogen and renewable energy technologies, assessing potential impacts on energy policy and regulation. Ultimately, this comprehensive analysis underscores the essential role of hydrogen co-firing in the energy sector and advocates for a comprehensive strategy that synergizes technological progress, economic viability, regulatory support, and public engagement to promote a resilient and sustainable energy future.

hydrogen co-firing↗

Ensuring Safe, Effective, and Reliable Use of Artificial Intelligence-Based Applications for Nuclear Electricity Generation through a Systems Approach

There is a significant potential to reduce operating and maintenance cost at nuclear power plants using artificial intelligence (AI) and machine learning (ML). For instance, AI/ML has the potential to significant improve work management processes, condition reporting, and plant surveillance activities. However, the nuclear industry has been slow in adopting AI/ML due to several multifaceted barriers discussed in this paper. This work presents such multidisciplinary approach intended to 1) accelerate industry adoption of AI/ML-based applications at nuclear power plants and 2) ensure their safe, reliable, and effective use. This approach is discussed further in this work and will be used to address overarching challenges associated with AI deployment at scale to provide industry guidance that support accelerated adoption of AI/ML technologies throughout the industry.

99 - GENERAL AND MISCELLANEOUS↗

Trustworthiness and Trust: Identifying Factors that Drive Successful Human-AI Interaction in Nuclear Power Plant Applications

Emerging technologies such as artificial intelligence (AI) and machine learning (ML) are rapidly evolving and considered a promising tool for efficient and continued safe operations of the U.S. nuclear power plants (NPPs). Emerging AI techniques like large language models (LLMs) are one such technology that may support personnel at existing NPPs perform work more efficiently. For example, operators may query the current operational status of a power plant via a chat interface leveraging LLMs to access plant-related information in an interactive manner rather than manually collecting various sensor data for tasks such as surveillances or completing work orders. This is a fundamental shift in the way operators currently perform their tasks today. The literature of human-automation interaction indicates that trust is a crucial factor that drives successful interaction between a human operator and an automated system, like an AI-infused NPP application. This work presents the results of a literature review on key factors that relate to trust in AI/LLM technologies for NPP applications. The relevant literature of human factors and cognitive engineering has identified various factors related to trust including trustworthiness, performance characteristics, operator skill and perceived risk. This preliminary literature review will guide development and evaluation of models involving the identified factors influencing trust in AI and develop a framework for human-centered design for interface between humans and AI. By addressing trust, this work supports developing a technical basis for designing key characteristics of AI/LLM to support calibrated trust, which will ultimately support wide-scale adoption of AI/LLM technologies, as well as ensure safe, effective, and reliable use.

99 - GENERAL AND MISCELLANEOUS↗

Frontier system-on-chip (SoC) technology for microwave diagnostics (invited)

The next generation of fusion reactors, exemplified by projects such as the Demonstration Power Plant following the International Thermonuclear Experimental Reactor, faces the monumental challenge of proving the viability of generating electricity through thermonuclear fusion. This pursuit introduces heightened complexities in diagnostic methodologies, particularly in microwave-based diagnostics. The increased neutron fluence necessitates significant reductions in vessel penetrations and the elimination of internal diagnostics, posing substantial challenges. SoC technology offers a promising solution by enabling the miniaturization, modularization, integration, and enhancing the reliability of microwave systems. After seven years of research, our team successfully pioneered the V- and W-band system-on-chip approach, leading to the development of active transmitters and passive receiver modules applied in practical settings, notably within the DIII-D tokamak project. Arrays of these modules have supported microwave imaging diagnostics. New physics measurement results from the Electron Cyclotron Emission Imaging system on DIII-D provide compelling evidence of improved diagnostics following the adoption of SoC technology. Furthermore, we achieved a breakthrough in developing an F-band SoC, advancing higher frequency capabilities for fusion devices. These achievements represent a significant leap forward in fusion diagnostic technology, marking substantial progress toward establishing reliable and efficient plasma diagnostics for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding Emerging Building Technologies in Federal Performance Contracting Markets

Every year, federal technology evaluation programs test and assess the performance of building technologies that are being considered for wider deployment in federal facilities. Despite these investments in technology validation, many of the technologies evaluated by federal programs struggle to achieve broad penetration into the federal performance contracting market. This report contains the results of a market-research survey conducted by the National Renewable Energy Laboratory to understand barriers to the wider adoption of validated building technologies in the federal performance contracting market and how this information can be used to increase their deployment. The initial phase of this research focuses on the energy service company community and the barriers they perceive to wider adoption of these evaluated technologies. The report ends with an examination of recommendations for how the U.S. Department of Energy's Federal Energy Management Program can assist agencies in deploying emerging building technologies through energy savings performance contracts.

25 ENERGY STORAGE↗

Community-Centric Microgrid Feasibility Analysis Framework to Accelerate Resilience of Island Communities

Marine energy offers a reliable energy solution for island and coastal communities, which often lack traditional local generation, to support their transition to energy independence and reduce reliance on externally imported fuels. Successful deployment of new technologies in these isolated locations requires community acceptance and approval from the outset, as these communities typically lack the financial and technical resources to operate and maintain new systems. This report presents a community-centric microgrid planning framework for remote coastal and island communities. Community engagement is integrated as the first step in the planning process, incorporating community profiles and visions into energy development scenarios. A case study was conducted in St. George, Pribilof Islands, Alaska, which relies entirely on diesel yet has significant wind and wave energy potential. Community engagement revealed a unique history and current economic status, with an interest in adopting advanced energy technologies despite past failures. Various microgrid configurations were optimized, considering different technologies to meet current and future energy needs while balancing cost and energy resilience. Wave energy converters (WECs) were a key component, integrated with other energy sources using the Xendee optimization tool. The Marine Energy Microgrid Toolkit, developed as part of this work, uses commercial power system analysis tools to optimize and analyze microgrid scenarios. The developed framework and toolkit can be applied to island and coastal communities to enhance resilience and support microgrid deployments. Future enhancements will include incorporating new marine resources, developing dynamic models, and automating the integration of Xendee and PowerFactory simulations.

02 PETROLEUM↗

Why Wideband Gap Needs Techno-Economics

The wideband gap community when discussing projects antidotally refers to the cost of the technology, frequently noting the higher wideband gap upfront cost in comparison to the incumbent state of art. Other technologies such as photovoltaics have embraced techno-economics analysis (TEA) as a method of analytically articulating the impacts of research advancements on system performance and lifetime costs. Our TEA shows the potential impact of research advancements on Gallium Oxide (Ga2O3) and Silicon Carbide (SiC) wafer manufacturing cost, the impact on the levelized cost of electricity (LCOE) when using a SiC based solar inverter, and lastly how the high cost of devices (SiC in this case) can be offset by other system cuts, such as the footprint and cooling reductions in a 1MW variable frequency motor drive. The specific goal is to show analytically the lifetime cost and performance benefits of adopting wideband gap technology whether it is at the device level or it is cumulative benefit though a simplified balance of system.

14 SOLAR ENERGY↗

Multiscale Experiments and Multiphysics Simulation of Multiphase Flow for Transportable Small Modular Reactors

A new type of safe, small, transportable nuclear reactor would address the intense and ever-growing global demand for energy produced via a resilient, carbon-free energy source. In this regard, transportable small modular reactors (SMRs) are being designed and developed for electricity generation within small/micro-grid/off-grid isolated systems, as well as for heat generation in industrial/residential applications. These reactors feature the capability to be fully factory fabricated and then directly transported to utilities’ sites as “plug-and-play” systems. Research and development (R&D) programs are underway at Idaho National Laboratory (INL) to successfully design, develop, and demonstrate such safe-by-design mobile reactor technologies, in collaboration with partner organizations. Multiscale experimental facilities and multiphysics simulation tools are required for reactor design verification and validation (V&V), and licensing. These advanced reactors are intended to feature passive safety systems such as passive containment cooling systems (PCCS), which consist of multiphase flows and multispecies distributions. This seminar talk will focus on designing and analyzing transportable SMR PCCS by using multiscale experiments and multiphysics computational fluid dynamics (CFD) simulations to support reactor licensing and safety. The corresponding research challenges are addressed via supportive verification and validation results generated by the models and simulation tools in combination with selective parametric and uncertainty analysis. This solution approach could blaze the trail for commercial adoption of such technologies. The facilities, simulation capabilities, and research opportunities available at INL in regard to such reactors and the integrated energy systems with which they go hand in hand are also discussed briefly, and may spark interest in deeper research as well as new collaborative projects.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Feasibility and Prospects of the High Resolution Rapid Refresh Model For Dynamic Line Rating

The ampacity of transmission lines is defined as the maximum amount of current the conductor can safely carry. It is necessary for transmission line operators to apply ampacity limits due to the thermal properties of the conductor. Dynamic Line Rating (DLR) is a technology and technique that uses the environmental conditions or a set of the conditions to calculate the ampacity of the conductor. The way the DLR is calculated has depended upon some amount of physical technology to implement the solution. The High Resolution Rapid Refresh (HRRR) Model is an atmospheric model that may provide enough resolution to perform dynamic line rating without any hardware at all. The objective is to use this model to perform Dynamic Line Rating. This will solve two of the most pervasive problems in Dynamic Line Rating, how to instrument a transmission line hundreds of miles long and then how to predict near future ampacity sufficient for transmission operators to effectively use, This technique will use the Idaho National Laboratory site as the test location for analysis. The High Resolution Rapid Refresh model is a reliable, freely available, and well-maintained weather forecasting model for the entire United States of America. The model provides enough special resolution that additional local weather monitoring devices at location are not necessary to conduct dynamic line rating. The HRRR ratings are lower on average than the locally measured ratings which allows for an additional margin of safety. The adoption of using purely digital methods for dynamic line rating could allow for wide scale adoption of the technology with very little overhead expenditure of implementation.

17 WIND ENERGY↗

The Industrial Efficiency and Decarbonization Office

The Industrial Efficiency and Decarbonization Office (IEDO) supports innovation technologies and the adoption of practices to enable the industrial sector to cost-effectively reduce greenhouse gas (GHG) emissions. IEDO and its programs are critical to putting the Nation on a pathway to reduce CO2 emissions by 50% by 2030 when compared to 2005 levels, and to achieve net-zero carbon emissions by 2050. With 30% of primary energy-related emissions attributable to the industrial sector, IEDO builds upon a foundation of energy efficiency as a decarbonization pathway to include process electrification, use of low carbon fuels and feedstocks, and carbon capture to meet industrial emissions reductions targets. IEDO provides planning, management, and direction necessary for a balanced national program of research, development, demonstration, technical assistance, and workforce development to drive energy, materials and production efficiency, and decarbonization across the industrial sector.

Energy-Intensive Industries, Cross-Sector Technolo↗

A Unified Testing Platform to Mature Blockchain Applications for Grid Emulation Environments

Blockchain technology is a relatively novel technology that can be used to develop more decentralized, autonomous and tamper-evident solutions. A feature that can aid Transactive Energy Systems to reach their goals by enabling individual actors to communicate and reach consensus with other participants in a more decentralized fashion. However, technical barriers to evaluate and adopt this type of technology within the electrical domain still exist. To facilitate this task, BLOSEM Unified Testing Platform (UTP), a DOE-sponsored, multi-lab effort intends to accelerate the development of solutions by offering a common set of reusable services that can be used to interconnect existent grid tools with blockchain services. UTP is intended to serve as development platform that can provide application engineers with the technical means to evaluate potential blockchain solutions, by enabling them to concentrate on the actual application functionalities while at the same time abstracting the connectivity and performance measurement tasks. The use of BLOSEM UTP is further demonstrated by implementing two potential use cases that are intended to validate both the feasibility of implementing these applications as blockchain-based solutions while also demonstrating the features provided by UTP.

blockchain co-simulation↗

A Cybersecurity Threat Profile for a Connected Lighting System

In anticipation of improved energy performance and cost savings, cities and building owners are increasingly considering “smart lighting initiatives” that aim to convert their collection of simple luminaires (i.e., lighting fixtures) into an intelligent connected lighting system (CLS) capable of remotely monitoring energy consumption and fault conditions, and possibly implementing adaptive lighting schemes. The U.S. Department of Energy (DOE) has set an national goal of tripling the energy efficiency and demand flexibility of the buildings sector by 2030, relative to 2020 levels 1. It is forecast that connected lighting systems can contribute to that goal by delivering 125 TWh of annual energy savings by 2035 2, equivalent to the annual output of 50 typical (500 MW) power plants. However, these energy savings and the DOE goal are put at significant risk if connected technologies are not adopted due to real or perceived cybersecurity concerns. Connected IoT devices such as these have historically been rife with vulnerabilities which sometimes put security considerations secondary to functionality and operability. What are the cybersecurity threats that will impact these systems, as formerly banal luminaires transition into intelligent connected devices that collect information about themselves, their surrounding environment, and possibly us? In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement. Fifty-seven threats were identified. Among our key findings: (1) 65% (37/57) of the threats did not involve the luminaires, but rather the other components needed to communicate with and manage them; (2) 63% (36/57) of the threats could have been mitigated through manufacturer-implemented defensive techniques or “controls”; and (3) 23% (13/57) of the threats were dependent on the network configuration. Recommendations based on the results of this work are made to key stakeholder groups. Notably, lighting technology developers are advised to address all threats that can be reasonably controlled with baked-in technology solutions (e.g., encryption or authentication controls), and employ some form of secure supply chain management and tracking where other parts (e.g., sensors, microprocessors) of a luminaire must also be built and manufactured with the proper security controls in place. Developers should also review threats involving assets not developed in-house to understand how connectivity with other devices will affect their product during system operation and determine if a compensating control for a defense-in-depth strategy will be needed. Finally, those interested in deploying CLS should compare the differences between cloud and on-premise models to determine which is more suitable for their needs and the abilities of their security team.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Microgrid's Role in Enhancing the Security and Flexibility of City Energy Systems

Smart cities depend on flexible and secure energy systems to ensure resilient power for critical infrastructure; however, recent weather-related events and cyberattacks have highlighted weaknesses in our energy systems, with the potential for widespread economic and security impacts. As stated by the Executive Office of the President, "the resilience of the US electric grid is a key part of the nation's defense against severe weather." To address the energy delivery security challenge, microgrids are rising as a viable solution that enhances the flexibility and resilience of the distribution grid and boosts the reliability of the local supply for the end-user. Traditionally, high capital investment has been a barrier to large-scale adoption of microgrid technology. Understanding the flexibility and resilience benefits of microgrids and accounting for the associated value streams can make the microgrid's proposition economically viable. In this chapter, microgrids' utility and their potential to serve as a flexible and resilient resource for the utility grid by providing capabilities such as peak shaving, demand response, and frequency regulation is presented. Moreover, other value streams, such as (1) their ability to island during a disaster and sustain critical loads which makes them a robust resilience solution for end-users, in the event of the utility grid outage and (2) microgrids also provide a flexible platform for integrating distributed energy resources in conjunction with storage and conventional generation technologies, strengthen microgrid's role in reducing the over-arching goal of emission reduction. Given the myriad of benefits associated with microgrids, we present strategies which can be employed for making microgrid itself resilient against physical and cyberthreats by employing hardware, software, and personnel training solutions to operate the microgrid before, during, and after a potential disaster. This chapter, thus, provides a holistic study of the microgrid as a resilience resource, for the utility grid, and a self-contained end-user for the end-user.

cyber-physical system↗

Method for Rapid Modeling of Distortion in Laser Powder Bed Fusion Metal Additive Manufacturing Parts

The simulation and modeling of part-level distortion and residual stress in diverse metal additive manufacturing (AM) geometries has great potential to enable the rapid adoption of this technology in engineering design. Moreover, the use of additive manufacturing component libraries (CLs) offer a computationally efficient means of quantifying these part-level defects resultant from AM processing. We report on how the individual simulations of simple shapes, potential entries in a CL, can be superimposed to provide an indication of distortion and residual stresses in complex geometries. Laser powder bed fusion AM was used to construct test geometries of varied shapes and their combinations in the form of CLs in an effort to characterize location-dependent and feature-dependent distortion distributions. Blue light scanning was used to experimentally measure 3D distortions in order to investigate the interaction between the component shapes and local boundary conditions. Overall, part-level distortions were highly dependent on test component geometry, local boundary conditions, and shape combination. Commercial finite element software was used to verify experimental trends and to make predictions of distortion. The use of CLs resulted in over 20 times savings in computational cost while reproducing overall trends in distortion for test geometry assemblies. Therefore, it is anticipated that the use of CLs for L-PBF AM geometries has demonstrated potential to facilitate efficient simulations of full component AM assemblies, thereby reducing the need for costly trial-and-error-type experimental analysis.

36 MATERIALS SCIENCE↗