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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Regional Representation of Wind Stakeholders' End-of-Life Behaviors and Their Impact on Wind Blade Circularity

Wind plant power has seen tremendous growth in the US and worldwide, representing the most significant renewable energy installed capacity besides hydropower. While wind power enables decarbonizing the electricity grid, the rising amount of end-of-life (EOL) wind blades - which are arduous to recycle - present a challenge for landfills if disposed of whole and a missed opportunity to recover valuable composite materials. The circular economy (CE) concept proposes strategies to rethink, reuse and recover products, components, and materials. However, transitioning to a CE implies changing how business models, supply chains, and behaviors deal with products and waste; changes arduously captured with traditional methods used to assess circularity such as life cycle assessment or material flow analysis (MFA). Here we present an agent-based model (ABM) that captures behavioral aspects impacting wind blade circularity in the US. The ABM also accounts for wind plant projects and landfills heterogeneity - a characteristic not easily included in top-down approaches such as MFA, input-output analysis, or system dynamics. Results show that recycling is divided as most recycling facilities are on the eastern side of the country, a challenge that could be alleviated by shredding blades before transportation. Recycling programs from the wind industry could also seed recycling behaviors within wind plant owners. Better yet, new blade designs could increase circularity if original equipment manufacturers accept the risks involved with the investments needed to adapt the production lines.

17 WIND ENERGY↗
DOE OSTI2022

Process mining for healthcare: Characteristics and challenges

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluating the incentive for soil organic carbon sequestration from carinata production in the Southeast United States

Soil organic carbon (SOC) can be increased by cultivating bioenergy crops to produce low-carbon fuels, improving soil quality and agricultural productivity. This study evaluates the incentives for farmers to sequester SOC by adopting a bioenergy crop, carinata. Two agricultural management scenarios – business as usual (BaU) and a climate-smart (no-till) practice – were simulated using an agent-based modeling approach to account for farmers’ carinata adoption rates within their context of traditional crop rotations, the associated profitability, influences of neighboring farmers, as well as their individual attitudes. Here, using the state of Georgia, US, as a case study, the results show that farmers allocated 1056 × 10 3 acres (23.8%; 2.47 acres is equivalent to 1 ha) of farmlands by 2050 at a contract price of $\$6.5$ per bushel of carinata seeds and with an incentive of $50Mg -1 CO2e SOC sequestered under the BaU scenario. In contrast, at the same contract price and SOC incentive rate, farmers allocated 1152 × 10 3 acres (25.9%) of land under the no-till scenario, while the SOC sequestration was 483.83 × 10 3 Mg CO2e, which is nearly four times the amount under the BaU scenario. Thus, this study demonstrated combinations of seed prices and SOC incentives that encourage farmers to adopt carinata with climate-smart practices to attain higher SOC sequestration benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas

Functional data analysis (FDA), which is a branch of statistics on modeling infinite dimensional random vectors resided in functional spaces, has become a major research area for Journal of Multivariate Analysis. We review some fundamental concepts of FDA, their origins and connections from multivariate analysis, and some of its recent developments, including multi-level functional data analysis, high-dimensional functional regression, and dependent functional data analysis. Here, we also discuss the impact of these new methodology developments on genetics, plant science, wearable device data analysis, image data analysis, and business analytics. Two real data examples are provided to motivate our discussions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Geospatial analysis of freight accessibility and job attraction: The role of interstate ramps, airports, ports, and rail

The number of jobs within an industry is significantly influenced by geographical location, with transportation infrastructure playing a key role. While previous research has largely focused on how access to jobs affects employment, less attention has been given to how transportation infrastructure impacts business operations and job attraction. Here, this study addresses this gap by examining how the ease of transporting products to key transportation facilities affects job numbers in freight-intensive industries. Using job data from the Longitudinal Employment Household Dynamics dataset at the Census Tract level, we applied a non-parametric model to assess the impact of proximity to interstate ramps, rail intermodals, ports, and airports. Our analysis revealed that closer transportation infrastructure generally has a greater impact on employment. Specifically, interstate ramps are crucial for attracting jobs, particularly in rural areas, while airport proximity is essential for industries dealing with high-value, time-sensitive goods, as seen notably in Massachusetts. The importance of transportation facilities varies considerably across states and industries. The findings and method in this study can be used by transportation agencies for freight planning.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Future energy infrastructure, energy platform and energy storage

Today fossil energy dominates energy consumption across the world. There has been an increasing momentum to reduce fossil energy consumption and increase renewable energy utilization to more than 70%. Such high penetrations of distributed renewable resources bring large uncertainty and complexity that cannot be easily handled by the current infrastructure. For the last two decades, telecommunication industry has gone through a similar transition from centralized to distributed systems, and more recently to platform approaches, which become the corner stone of today’s vibrant platform economy. Based on telecommunication history, we believe that a platform-based approach, called the energy platform, is a viable solution for addressing the renewable energy challenges. The energy platform consists of an array of computational algorithms, sensing and control technologies for key industry, energy generators and users to jointly manage and control the complex energy infrastructure. It includes the following key components: (1) the hardware and software to generate, store, control and transmit electricity/data (the energy cloud), (2) the digital platforms and tools for key energy producers, digital, service and communication industry to share the assets, participate in and manage the complex infrastructure, and for customers to participate in energy transactions, (3) the transaction platform for new service and business models. Additionally, the energy platform requires breakthroughs in large scale energy storage and many other areas including efficient power electronics, sensors and controls, new mathematical and computational tools, and deep integration of energy technologies and information sciences to control and stabilize such complex chaotic systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Idaho national laboratory to demonstrate collaboration first versus competition to accelerate achieving a secure clean energy future by 2031

Idaho National Laboratory (INL) announced at COP27 it would reach net zero greenhouse gas (GHG) emissions by 2031. As a Nuclear, Energy and Environment, and National Homeland Security laboratory, the predominant solution to closing the clean energy gap will include nuclear as a safe, clean, reliable and affordable electricity source with the additional benefit of producing heat and hydrogen to fuel INL’s large transportation fleet. INL’s collaboration first vs. competition is essential to the program’s success. The focused actions in INL’s Nuclear Roadmap include: Infrastructure, Licensing/Regulatory, Financial, Time to Market, Fuel Cycle and Public Confidence/Communications. The roadmap also includes nuclear technology innovations and creative partnerships with utility providers, regulators, businesses, community members, and Indigenous Peoples to accelerate deployment of advanced reactors. Through development of the Net-Zero Nuclear Roadmap, INL will offer a model to provide safe and secure energy for the nation and the world by: (1) establishing the necessary infrastructure on its 890-square mile site to support demonstration, (2) showing proven pathways through the licensing and regulation process, (3) partnering with utilities to ensure commercial application, and (4) collaborating with industry to site new technologies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Accelerating nuclear-integrated data center pursuits in the USA: SWOT analysis, power-thermal management strategies and demonstration plan

Here, this study explores the increasing interest in leveraging nuclear power to meet the escalating energy demands of data centers in the United States (U.S.) by focusing on key factors that contribute to accelerated deployment. The study highlights the importance of N+1/N+2 power supplies (where N is the required number of units), outlines research and innovations in nuclear-integrated data center thermal management and demonstration plan. It also provides updates about status and costing of various reactor system designs. A summarized strengths, weaknesses, opportunities, and threats (SWOT) analysis shows the potential options for grid connectivity, reactors, and site selection. Suitable site discussions consider land and water availability, grid access, and optical fiber connectivity, and the study presents graded prospects for Department of Energy (DOE) sites with a specific example. Community engagement and partnerships are emphasized, particularly the roles of local government, federal agencies, utilities, and data center industry partners, which are crucial for accelerating deployment, business outreach, and approvals. The study provides actionable insights for stakeholders to accelerate the deployment of nuclear-powered data centers.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2020

A large-scale, agent-based simulation of metropolitan freight movements with passenger and freight market interactions

This study summarizes the first stage in the implementation of an agent-based freight modeling system that has a global representation of agents and detailed modeling of a large-scale transportation network. The model is used to evaluate the transportation and energy impacts of goods movement across urban and national scales. The framework is implemented within POLARIS, a C++-based Planning and Operations Language for Agent-based Regional Integrated Simulation, which consists of an activity-based modeling (ABM) and dynamic traffic assignment (DTA) system that has robust features for passenger travel. This platform provides a tool to model interactions among consumers, producers, and the transportation system. The main objective of this initial implementation is to implement a freight model within POLARIS following an agent-based paradigm with behavioral and simulation methods. This paper presents the initial framework and illustrates the application of the model. Building upon earlier works, a parcel location assignment algorithm for business establishments in the population is documented, along with a method for estimating establishment production and consumption volumes. In addition to population generation, other features of the model include push-pull supply chains, multimodal path choice, choice of transportation logistics node, and dynamic traffic assignment. A module with e-commerce supply and demand was also developed to analyze the effects of e-commerce delivery on last-mile energy use and congestion.

agent-based freight↗
DOE OSTI2025

Roadmap to an electron beam or X-ray center for industrial applications

Here, this paper introduces the topics that need consideration to allow an effective feasibility analysis of electron beams and/or X-rays technologies prior to potential investment and implementation of these technologies for industrial applications. It also highlights considerations for planning, developing and construction of an electron beam or X-ray facility The focus of this paper is on business topics and it provides details of where additional technical information can be found. The paper also describes current applications for electron beam and X-ray technologies to demonstrate their potential.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

A framework and calculator for evaluating the impacts of shelf life extension and other food loss and waste reduction technologies

Optimization of the food supply chain (FSC) depends on reducing food waste, especially at the consumer stage, where a substantial portion of food is not eaten, but instead disposed of via landfill, incineration, or in-sink disposals. One key strategy is to increase the time that consumers have before food goes bad or expires. This study developed a framework to assess the efficacy of shelf-life extension (SLE) technologies for mitigating food loss and waste (FLW), such as packaging improvements. The impact flows through the entire FSC, reducing FLW, energy use, and other inputs at each stage. The framework and resulting calculator can be used to evaluate the impact of FLW reduction at any stage for any food commodity. As shown by two SLE cases, the calculator is valuable for policy-makers, government entities, and professionals, specifically those in marketing, business development, and capital projects teams, to comprehensively evaluate the impacts of FLW reduction technologies and practices. The framework and calculator are sensitive to the shape of the consumption curve, the fraction of inedible waste, and the current shelf life. The calculator was used to assess the impacts of the United States goal of reducing food waste by consumers through various SLE lengths. It was found that uptake of several near-ready-to-deploy SLE technologies would reduce annual food production demand by about 10–19 MMT and supply chain energy consumption by 240–410 PJ in the United States.

Food loss and waste (FLW)↗
DOE OSTI2026

Heliostat sizing methodology for concentrating solar thermal industrial process heat projects

This study presents a method to obtain a heliostat size that minimizes the levelized cost of heat (LCOH) of a heliostat-based concentrating solar thermal system for applications of solar heating for industrial processes at operating temperatures from 565 to 1550°C. The method extends prior work by embedding a routine for system design that obtains near-optimal subsystem sizes, increasing the fidelity of drive cost functions, and adding an optical performance model to supplement the previously developed cost models, which we update to reflect current pricing trends. An illustrative business case is developed for Daggett, California, targeting specified annual thermal energy outputs of 50 to 400 GWh th . Optical performance is modeled using verified estimates from the literature. A surrogate heliostat cost model, derived from commercial heliostat designs and scaled for production volume, installation, and operations and maintenance costs, is used to develop cost functions. Results show that heliostat size strongly affects the LCOH, producing a characteristic U-shaped trend with a robust near-optimal window of 7-20 m 2 ; the heliostat size producing the lowest project cost in our study grows slightly as the project size increases, and is reduced as the operating temperature increases. The findings in this study are consistent with the general trend of smaller heliostats being deployed at existing projects for high-temperature industrial process heat and reflect the significant reduction in power electronics and other per-heliostat costs. The methodology we propose is general and can be tailored to revised cost curves as the technology continues to evolve.

14 SOLAR ENERGY↗
DOE OSTI2024

Ecologically inspired metrics for transitioning to a sustainable and resilient circular economy with application to multilayer plastic films

Current Circular Economy (CE) frameworks applied to product chains exhibit notable shortcomings. These include neglecting the resilience and robustness of design, requiring detailed economic and environmental data for impact assessment, and relying on qualitative rather than quantitative metrics capturing certain CE design aspects. In the current contribution, we addressed these shortcomings by developing an Ecologically inspired (Eco-inspired) Framework using the mathematical foundations of Ecological Network Analysis (ENA). While ENA metrics have previously found application in designing circular economies, particularly in Industrial Symbiosis (IS) networks, our adaptation tailors these metrics for use in product-level CE, recognizing the inherent distinctions between product-level CE and IS. Our Eco-inspired Framework comprises three key categories to provide holistic and granular-level metrics for designing product-level CE. The first set of metrics assesses circularity and resource efficiency. The second set gauges network intensity and robustness as complementary indicators ensuring a CE is both sustainable and resilient. The third group of metrics evaluates enhancement potential of CE strategies through introducing quantitative metrics for measuring the degree of closed-loop strategies and average circularity level of a CE design. The three comprehensive set of indicators within the Eco-inspired Framework uniquely captures various facets of circular design, whether originating from technological innovations and recovery improvement at the end of life (EoL), shifts in human consumption patterns, alterations in product design, or changes in business models. The framework’s application is tested in designing a CE for multilayer Polyethylene-Polyamide (PE-PA) films. Using the Eco-inspired Framework, we identified the best strategy for designing a resilient and sustainable CE for PE-PA films. A diverse set of EoL strategies along with a reduction in product consumption can improve circularity and resilience by 650% and 255%, respectively, and mitigate greenhouse gas emissions by 90%. The framework minimizes trade-offs between sustainability and circularity goals and offers insights on how to enhance each strategy for achieving a resilient and sustainable CE for products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Taming the wild edge of smart grid – Lessons from transactive energy market deployments

For two decades, the idea of using market-based approaches in field deployments that coordinate the flexible operation of electricity customer assets has occupied the efforts of transactive energy practitioners. While the purported benefits of this distributed decision-making approach have been well explored, the practical aspects of implementing such a system to address real-world problems are just beginning to emerge. This report surveyed 24 field-deployed programs and interviewed experts instrumental in these deployments. The results of the survey and interviews reveal the diversity of designs and applications. They highlight the technical promise of the approaches as well as challenges with system integration, sustainable business strategy, and regulatory policy obstacles. Insights from the survey offer considerations to direct future effort and investment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

On the evaluation and selection of network-level traffic control policies: Perimeter control, TUC, and their combination

Perimeter control (PC) of urban traffic networks can be effective in increasing network-wide efficiency. PC operates on the border of a protected region of a traffic network. Most studies thus far considered fixed-time plans for the inner part of these regions. A few studies have shown that combining PC with locally actuated or decentralized traffic control systems may have positive effects on traffic performance, including better-defined Network Macroscopic Fundamental Diagrams (NMFDs), increased network throughput, and reduced delays. The Traffic-responsive Urban Control (TUC) is a real-time network-wide traffic control system with particular design characteristics, such as the balancing of link's occupancies and an inherent gating feature. These characteristics suggest that TUC may enhance the traffic network performance when combined with PC whilst improving the resulting NMFDs and network throughput and delays. Here, in this work, we investigate the effect of feedback perimeter control (FPC), TUC, and their combination on the NMFD and on the traffic conditions of general traffic and public transport in the microsimulation of a realistic model of the Christchurch Central Business District in New Zealand. We perform a thorough investigation of practical aspects of both control strategies and their combination, including parameter tuning and infrastructure requirements, and how they may affect the control system choice. Results show higher throughput and less hysteresis on the NMFDs, particularly when TUC is involved. PC provides benefits concentrated in the protected region which can greatly benefit public transportation if there is an overlap with the transit network. The combination of TUC and FPC boosts network-wide throughput.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

42 ENGINEERING↗
DOE OSTI2020

LIGHT DUTY VEHICLE CHOICE MODELS EXAMINING ALTERNATIVE FUEL TECHNOLOGY PREFERENCES AMONG COMMERCIAL FLEET OWNERS

Agent-based transportation models are critical tool for evaluating energy use, emissions and mobility impacts of transportation. In this context, vehicle ownership models are critical for linking agent activities to their impacts on the transportation system. However, no agent-based freight transportation models to date has been developed that predicts the fuel technology that is preferred by establishments when purchasing a Light Duty Vehicle (LDV) for business purposes. This research addresses this gap by using recently collected survey data to estimate a discrete choice model that can be applied in the agent-based context.

commercial↗