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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 289 records · Page 16

Urban Energy Systems: Research at Oak Ridge National Laboratory

In the coming decades, our planet will witness unprecedented urban population growth in both established and emerging communities. The development and maintenance of urban infrastructures are highly energy-intensive. Urban areas are dictated by complex intersections among physical, engineered, and human dimensions that have significant implications for traffic congestion, emissions, and energy usage. In this chapter, we highlight recent research and development efforts at Oak Ridge National Laboratory (ORNL), the largest multipurpose science laboratory within the U.S. Department of Energy’s (DOE) national laboratory system, that characterizes the interactions between the human dynamics and critical infrastructures in conjunction with the integration of four distinct components: data, critical infrastructure models, and scalable computation and visualization, all within the context of physical and social systems. Discussions focus on four key topical themes: population and land use, sustainable mobility, the energy-water nexus, and urban resiliency, that are mutually aligned with DOE’s mission and ORNL’s signature science and technology capabilities. Using scalable computing, data visualization, and unique datasets from a variety of sources, the institute fosters innovative interdisciplinary research that integrates ORNL expertise in critical infrastructures including energy, water, transportation, and cyber, and their interactions with the human population.

Bhaduri, Budhu↗

BioSecure Digital Twin: Manufacturing Innovation and Cybersecurity Resilience

U.S. national security, prosperity, economy, and well-being require secure, flexible, and resilient Biopharmaceutical Manufacturing. The COVID-19 pandemic reaffirmed that the biomedical production value-chain is vulnerable to disruption and has been under attack from sophisticated nation-state adversaries. Current cyber defenses are inadequate, and the integrity of critical production systems and processes are inherently vulnerable to cyber-attacks, human error, and supply chain disruptions. The following chapter explores how a BioSecure Digital Twin will improve U.S. manufacturing resilience and preparedness to respond to these hazards by significantly improving monitoring, integrity, security, and agility of our manufacturing infrastructure and systems. The BioSecure Digital Twin combines a scalable manufacturing framework with a robust platform for monitoring and control to increase U.S. biopharma manufacturing resilience. Then, the chapter discusses some of the inherent vulnerabilities and challenges at the nexus of health and advanced manufacturing. Next, the chapter highlights that as the Pandemic evolves, we need agility and resilience to overcome significant obstacles. This section highlights an innovative application of Cyber Informed Engineering to developing and deploying a BioSecure Digital Twin to improve the resilience and security of the biopharma industrial supply chain and production processes. Finally, the chapter concludes with a process framework to complement the Digital Twin platform, called the Biopharma (Observe, Orient, Decide, Act) OODA Loop Framework (BOLF), a four-step approach to decision-making outputs from the Digital Twin. The BOLF will help end users leverage twin technology by distilling the available information, focusing the data on context, and rapidly making the best decision while remaining cognizant of changes that can be made as more data becomes available.

99 GENERAL AND MISCELLANEOUS↗

BETO 2021 Peer Review - 1.3.2.001 - Algae Biomass Composition

Addressing critical improvements in biomass productivity and associated biochemical composition is a priority for the economic and sustainable commercial development of biofuels and bioproducts from algae. Capitalizing on pathways that integrate engineering approaches with fundamental biochemistry of photosynthetic organisms will lead to a better understanding of the complex nexus of algae growth rates, productivity and composition. This project focuses on identifying the critical factors for economic development of fuel and bioproduct technologies. Algal compositional characteristics form the foundation of robust economic and business models. This project supports that foundation by developing and validating accurate compositional methods and disseminating them to the greater community. Simultaneously, we build a deep understanding of the dynamic biochemical composition and carbon allocation for biomass value and conversion yields. A co-product portfolio developed under this project demonstrated a 30% increase in intrinsic value. Additionally, an integrated pipeline of molecular diversity mapping for product discovery with quantitative demonstration across species was deployed over the BETO algae program. The advances made here are highly relevant to BETO's multi-year program targets of reducing costs and integrating dynamic biomass composition with conversion processes to provide options for bioproducts, all leveraging the molecular diversity of algae.

algal compositional characteristics↗

Sunshine, Wine, and Wool - Agrivoltaics in Texas' Energy Transition

Achieving Texas' renewable energy goals while maintaining land for agriculture requires strategic cross-sector collaboration. In this session, researchers, ranchers, and developers will discuss opportunities and challenges at the energy-agriculture nexus - specifically, emerging trends in agrivoltaics, Texas-relevant considerations, R&D opportunities, and the potential role of agrivoltaics in Texas' energy transition.

agriculture↗

Trends, Insights, and Considerations for Agrivoltaics in the Northeast: Applying National Lessons Learned to the Case of Pennsylvania

There are unique challenges and opportunities at the nexus of agriculture and energy. This presentation will feature a social science overview of agrivoltaics, which is the practice of combining solar energy and agricultural production on the same land. Centering on recent research and commercial insights, this presentation will discuss the implications of lessons learned in the Northeast and highlight key considerations for future agrivoltaic R&D in Pennsylvania.

agriculture↗

Simulating the Phonon Collection Efficiency in KIPMDs

Kinetic inductance phonon-mediated (KIPM) detectors use microwave kinetic inductance detectors (MKIDs) to read out phonon signals in the substrate. They are a promising class of detectors to be used in light dark matter (DM) searches due to their potential eV-scale sensitivity and native frequency-domain multiplexability. In order to improve upon the design of these detectors, simulations are needed to understand the effects of detector design on measurable physical parameters including the phonon collection efficiency, $\eta_{ph}$, which is defined as the ratio of phonon energy detected by the sensitive target element to the incident energy deposited in the substrate. This work simulates the phonon collection efficiency for a KIPMD currently operated at the Northwestern EXperimental Underground Site (NEXUS).

Dang, Stella Q.↗

Machine Learning Digital Twin for Lithium Ion Battery State of Health Predictions

A digital twin system has been established to model the long term degradation of the state of health of lithium ion batteries. Two data streams result from the computational model of the system and from the physical experiment measurements. A machine learning pipeline has been developed at the nexus of these data streams. Leveraging the unique data sources in multiple transfer learning approaches has lead to the development of multiple cell specific machine learning digital twins. Our discussion on this first of its kind technology will cover challenges in data ingestion, scalability, architecture and orchestration, and research findings.

25 - ENERGY STORAGE↗

DeepLynx Ecosystem 2025

Poor data integration and governance continue to plague complex engineering projects, resulting in missed cost, schedule, and performance targets. Departments operate in isolated systems with manual data exchange, creating fragmented information that compounds errors and leads to significant delays and cost overruns. The DeepLynx ecosystem addresses these challenges through an open-source, modular data management platform that transforms fragmented project data into an integrated digital thread. Built on a federated microservice architecture, the ecosystem comprises seven specialized tools centered around DeepLynx Nexus, a unified data catalog with hierarchical organization and graph-based navigation capabilities. The ecosystem includes: DeepLynx Stream for real-time timeseries data ingestion from industrial sources; DeepLynx Ingest for governed data uploads with formal review workflows; DeepLynx Lattice for ontology-based entity and relationship extraction; DeepLynx Run for workflow orchestration and secure AI/ML compute; DeepLynx Visualize for 3D digital twin visualization; and DeepLynx Insight for AI-assisted document analysis with traceable, grounded responses. Deployable in cloud, on-premise, or hybrid environments using containerized Docker applications and Helm charts, the DeepLynx ecosystem provides flexible infrastructure that adapts to organizational requirements. By consolidating project data into a unified data lake with role-based access controls and OAuth2 authentication, DeepLynx enables digital thread and digital twin capabilities that improve decision-making, reduce risk, and support complex engineering workflows throughout the project lifecycle.

42 - ENGINEERING↗

Real-Time Detection of Charge Jumps in Superconducting Qubits with a Convolutional Neural Network

Ionizing radiation from cosmic rays and gammas can induce discontinuous jumps in the environmental charge of superconducting qubits (charge jumps), causing correlated errors that challenge fault-tolerant quantum computing while simultaneously providing a detection signature for quantum sensing applications. Current detection methods operate offline, introducing latency incompatible with in-the-loop qubit control. In this paper, an online detector of charge jumps for superconducting qubits, based on a dilated causal convolutional neural network (DCCNN) designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, is presented. The network is trained on synthetic Ramsey tomography scans generated from qubit templates measured at the Northwestern Experimental Underground Site (NEXUS) at Fermilab, and translated to FPGA firmware via hls4ml with ap_fixed$\langle 16,6 \rangle$ quantization, reaching a per-inference latency of $6.19 μ$s on the Zynq UltraScale+ RFSoC ZCU216. At this operating point the DCCNN matches the detection efficiency of the established offline $χ^2$ algorithm ($0.843 \pm 0.022$ vs. $0.866 \pm 0.020$ on $|Δq| \in [0.1, 0.5] e$ at matched false-positive rate), while requiring no per-qubit hyperparameter tuning. This shifts charge-jump detection from a post-hoc diagnostic to a control-loop primitive, enabling adaptive protocols that respond to radiation-induced events in situ, with applications to quantum-computing error mitigation and to the use of superconducting qubits as particle detectors.

Gaytan-Villarreal, Daniel [Carnegie Mellon U.]↗

NXREFINE

NXRefine implements a complete workflow for both data acquisition and reduction of single crystal diffuse x-ray scattering collected as a series of area detector frames during continuous sample rotation. The data are stored in HDF5 files, which conform to the NeXus data format standard. These files contain a comprehensive set of metadata, including the incident wavelength, powder calibration scans used to define detector distances, beam centers, and yaw, pitch, and roll corrections. Automated peak searches of the three-dimensional data arrays define a set of Bragg peaks that are used to define an orientation matrix, defined according to Busing and Levy, which is then used to transform the data from angular coordinates to reciprocal space coordinates using the CCTW program. Multiple rotations at different detector translations and offset rotation axes are combined to ensure that there are no gaps in the reconstructed data, and allow the construction of masks to eliminate detector artifacts due to Compton scattering within the sensor layers. Finally, the data can be transformed into 3D-ΔPDF maps using the punch-and-fill method after symmetrization.

OSBORN, RAYMOND↗

Integrated Urban Services: Program Impact and Business Plan Summary

The Integrated Urban Services (IUS) program, launched in 2021 and funded by the U.S. State Department under the United States-Association of Southeast Asian Nations (US-ASEAN) Smart Cities Partnership, aimed to bolster resilience in ASEAN cities by addressing challenges across food, energy, and water systems. Led by the National Renewable Energy Lab (NREL) with support from Regenerative Impact Ventures, the program focused on demonstrating the socio-economic benefits of integrated urban planning, educating stakeholders on circular economy principles, providing technical assistance to two ASEAN cities, and attracting private sector involvement. The program facilitated peer learning events, engaging public and private sector participants and leveraging knowledge from a group of global experts to inform approaches and best practices. Technical assistance was provided to two pilot cities, Iskandar Malaysia and Cagayan de Oro, Philippines, resulting in the development of market-driven business plans for resilient, circular, and regenerative energy-water-food system projects. The Iskandar Malaysia pilot focused on development of a state-of-the-art AgriTech Innovation Hub and Modern Farming Complex to enhance agricultural productivity and produce enough renewable energy to power the facilities. The Cagayan de Oro project aimed to enhance urban agricultural productivity and waste management through development of an Urban Precision Agricultural Complex featuring aeroponics, hydroponics, aquaponics, agrivoltaics, and a Black Solider Fly Facility for converting municipal solid waste into commodities. The success of the IUS program sets a precedent for replicating integrated urban service models globally, offering valuable insights for cities aiming to enhance their resilience and sustainability.

ASEAN↗

Life cycle assessment of novel heat exchanger for dry cooling of power plants based on encapsulated phase change materials

Cooling systems in power plants account for approximately 40% of total freshwater withdrawals in the U.S. Due to dwindling access to freshwater resources worldwide, continued operation of wet cooling systems poses a significant engineering challenge. To reduce water consumption, a novel air-cooled heat exchanger has been developed using encapsulated phase change material (EPCM) for dry cooling of power plants. Compared to traditional finned-tube air-cooled condensers, this novel EPCM heat exchanger improves the heat transfer coefficient and power plant efficiency while reducing the pressure drop and cooling system cost. Life cycle assessment (LCA) and techno-economic analysis (TEA) are used to evaluate the environmental and economic performance of EPCM heat exchangers from cradle-to-grave and to compare them to wet cooling and traditional air-cooled condensers. A thermodynamic model is developed to predict the EPCM heat exchanger performance for plant-scale operations. Equipment and construction costs for heat exchangers are estimated based on design parameters obtained from the thermodynamic model. Both process-LCA and economic-input–output LCA are used to simulate and test the sensitivity of EPCM alternatives with commercial wet and dry cooling technologies. We investigate options for EPCM end-of-life management upon retiring the heat exchanger and construct a process-based LCA model to estimate a greenhouse gas (GHG) emissions credit for recycling the EPCM. The life cycle GHG emission of the novel dry cooling technology is 1.16 kg CO 2 eq. /MWh compared with the 1.1–4.3 kg CO 2 eq. /MWh reported for commercial dry cooling technologies and consumes 9.5 L/MWh e of water for cradle-to-gate life cycle, which is significantly lower than that of wet cooling systems. The TEA shows many advantages of EPCM cooling technology over the state-of-art dry cooling solutions. Overall, the EPCM heat exchanger provides a better alternative compared to existing dry cooling and wet cooling technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Supercritical water desalination and oxidation (SCWDO): Effectiveness on complex solutions, technoeconomic, and CO 2 impact for produced water treatment

The modern energy-economy is increasingly causing the production of highly saline brines, including from produced water. Supercritical water desalination can concentrate and extract minerals from these brines, but the effects of mixed salt interactions, organic degradation with additives, and the technology's economics are not well understood at supercritical condition. The present study evaluated and experimentally studied an integrated supercritical water desalination and oxidation (SCWDO) process for treating real-produced water samples from oil/natural gas field. The complex interactions between the various anions and cations in produced water were extensively evaluated. Most of the divalent and trivalent ions were extracted below 250 °C while the majority of the monovalent salt were removed between 380 to 410 °C. The treated real produced water was of drinking water quality, with <500 mg/l of total dissolved solid (TDS) and with 100% organics removal. Furthermore, the heat liberated during the organic oxidation could be utilized internally and for electricity generation for enhanced the energy efficiency and lower cost of produced water treatment. With system optimization, the proposed SCWDO process can essentially be made a net zero energy process. A novel process flow diagram for the commercial scale self-powered hybrid SCWDO technology was proposed as a cost-effective produced water treatment to mitigate the environmental crises. Techno-economic analysis showed that produced water treatment cost with SCWDO can be reduced to 2–3 $/m 3 and can be up to 60 % cheaper to traditional deep well reinjection. Additionally, the proposed SCWDO process could achieve net negative CO 2 emission.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Hydropower and environmental flow management: System-level trade-offs at Glen Canyon Dam

The research focuses on the Colorado River Basin, specifically examining the Glen Canyon Dam (GCD) and its influence on surrounding aquatic ecosystems. This area is crucial due to its role in hydropower production and its impact on downstream environments, including the Grand Canyon National Park. This study explores the integration of environmental factors into hydro dispatch modeling at GCD to tackle ecological challenges posed by the invasive smallmouth bass (SMB). Utilizing the GTMax SL and SERM models, the research assesses the effects of SMB control experiments on hydropower generation, economic value, and grid stability. The study examines the financial and economic impacts of bypass flows designed to release colder water to prevent SMB spawning, which can significantly reduce hydropower output and increase costs. The research identifies that declining reservoir levels and rising water temperatures in Lake Powell have facilitated SMB spawning, posing a threat to native fish populations like the endangered humpback chub. The findings highlight the importance of adaptive management strategies to balance ecological preservation with hydropower generation amid long-term weather-related challenges. The study underscores the need for comprehensive assessments of flow options to prevent SMB establishment below GCD, considering the broader implications for sediment dynamics and ecological interactions.

Ecological impact assessment↗

Cooperation or Rivalry? Impact of alternative development pathways on India's long-term electricity generation and associated water demands

The world has witnessed a significant shift in the last decade in the way countries interact with each other. A cooperation based international paradigm is being challenged by countries engaging in rivalry with each other in the name of their national interests. What developmental pathway the world charts in the future is going to be path defining for global energy and emissions use. India, expected to play a critical role in the emissions mitigation debate, would contribute to and would be impacted by these pathways. In India specific literature, however, little attention has been paid to development pathways related uncertainties and their impact on energy futures. We seek to address this gap by modelling India's electricity futures and associated water demands under different development pathways. Our analysis shows that alternative development pathways would have significantly different implications for the energy access, electricity generation mix, associated water withdrawals, and carbon dioxide emissions in India. We conclude by arguing that energy, emissions and water policies should be conceived with an explicit understanding of uncertainties related to potential development pathways that the world and India can chart.

India, Electricity-Water Nexus, Development Pathwa↗

Can we have clean energy and grow our crops too? Solar siting on agricultural land in the United States

We report a record amount of large-scale solar development is proposed and under construction in the US Midwest, much of it on agricultural land. This article contributes to the social science literature on renewable energy and public acceptance by addressing stakeholder perspectives on developing utility-scale solar power on agricultural land and complex institutional dynamics that shape these siting decisions. How do stakeholders’ interactions coproduce solar siting decisions? How are the existing complex contexts of energy and agricultural systems affecting solar siting? Who are the stakeholders involved in agricultural solar siting, and how do their epistemic paradigms about using agricultural land, especially prime farmland, differ? To answer these questions, interviews were conducted and analyzed across energy, agriculture, government, and expert stakeholder groups, focusing on Michigan, with comparison to other states. The results provide a conceptual map of stakeholder interaction related to solar development on farmland and characterize the main epistemic paradigms shaping stakeholder conflict. Issues shaping agricultural community perceptions include identity and farmland, the decisions of local farmland renters and non-operating landlords, prime versus lower quality farmland, farm financial viability, and farmland as private property or a public good. Some scientists and engineers seek to alleviate conflicts and drawbacks of agricultural land conversion for solar use by combining farming and solar energy generation: a practice called agrivoltaics. We argue that agrivoltaics are currently treated as a technological fix by not accounting for stakeholder interaction in complex policy, community, and scientific institutions. We conclude by identifying interdisciplinary research priorities to develop socially robust designs.

14 SOLAR ENERGY↗