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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CSP Plant Construction, Start-Up, and O&M Best Practices Study

There are currently 90 operational CSP plants of 10 MW or larger located throughout the world, primarily in Spain, U.S., MENA region, South Africa, and China. In 2018, the U.S. Department of Energy (DOE) funded Solar Dynamics, under subcontract to NREL, to investigate and document lessons learned and best practices associated with the construction, start-up, and operations phases of a majority of these plants. DOE funding for the effort was leveraged by additional funds provided through SolarPACES and the World Bank. This information was obtained by interviewing key stakeholders representing CSP plant owners, operators, construction companies, vendors, technical advisors and financers of these systems, and will be published as an NREL Technical Report at the completion of the project. This paper provides an overview of key challenges facing today's CSP parabolic trough and power tower technologies during all the phases mentioned above.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

Hybrid renewable energy systems

In the pursuit of ecologically sustainable and resilient energy systems, increasingly more attention is being devoted to a diversity of energy generation and storage methods. As the landscape of generation technology gains nuance and complexity, a wide-ranging set of technical questions has emerged, touching on topics that range from control and optimization of hybrid systems to finance and economic viability to multi-fidelity modeling and scientific machine learning. In the context of this special issue, hybrid renewable energy systems are any systems that consider the combined dynamics of more than one form of generation, storage, or grid subsystem. Research endeavors have delved into improving the flexibility of energy systems by utilizing existing resources, introducing novel operational strategies, deploying enhanced renewable forecasts, and exploring emerging technologies. In conclusion, the interconnection among various sectors has garnered heightened attention, not only due to the provision of additional tradable energy products but also for furnishing flexible headroom to system operators.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Solving high-dimensional partial differential equations using deep learning

Developing algorithms for solving high-dimensional partial differential equations (PDEs) has been an exceedingly difficult task for a long time, due to the notoriously difficult problem known as the “curse of dimensionality.” This paper introduces a deep learning-based approach that can handle general high-dimensional parabolic PDEs. To this end, the PDEs are reformulated using backward stochastic differential equations and the gradient of the unknown solution is approximated by neural networks, very much in the spirit of deep reinforcement learning with the gradient acting as the policy function. Numerical results on examples including the nonlinear Black–Scholes equation, the Hamilton–Jacobi–Bellman equation, and the Allen–Cahn equation suggest that the proposed algorithm is quite effective in high dimensions, in terms of both accuracy and cost. Furthermore, this opens up possibilities in economics, finance, operational research, and physics, by considering all participating agents, assets, resources, or particles together at the same time, instead of making ad hoc assumptions on their interrelationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An overview of the fusion landscape

Fusion is very attractive as a potential energy source, but it is taking a long time to develop into a commercial reality. Given the challenges of climate change and the need for dispatchable power as a complement to renewable energy sources that vary on daily and seasonal timescales, there is great enthusiasm internationally to accelerate the commercialization of fusion energy. Forty-five private companies around the globe, with total financing of $7.1 billion, are engaged in the development of fusion energy. In the United States, the White House has put forward a “Bold Decadal Vision for Commercial Fusion Energy,” with bipartisan support from Congress. To develop commercial fusion energy, certain goals must be met. In conclusion, a wide variety of approaches are being pursued to meet these goals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

A formal method for identifying distinct states of variability in time-varying sources: SGR A* as an example

Continuously time variable sources are often characterized by their power spectral density and flux distribution. These quantities can undergo dramatic changes over time if the underlying physical processes change. However, some changes can be subtle and not distinguishable using standard statistical approaches. Here, we report a methodology that aims to identify distinct but similar states of time variability. We apply this method to the Galactic supermassive black hole, where 2.2 μm flux is observed from a source associated with Sgr A* and where two distinct states have recently been suggested. Our approach is taken from mathematical finance and works with conditional flux density distributions that depend on the previous flux value. The discrete, unobserved (hidden) state variable is modeled as a stochastic process and the transition probabilities are inferred from the flux density time series. Using the most comprehensive data set to date, in which all Keck and a majority of the publicly available Very Large Telescope data have been merged, we show that Sgr A* is sufficiently described by a single intrinsic state. However, the observed flux densities exhibit two states: noise dominated and source dominated. Our methodology reported here will prove extremely useful to assess the effects of the putative gas cloud G2 that is on its way toward the black hole and might create a new state of variability.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Tokamak Energy’s pre-concept design for a fusion power plant: an overview of ST-E1

Climate change and rapidly rising energy demand, driven in part by artificial intelligence and data-centre growth, create an urgent need for stable, low-carbon, and abundant power. Fusion is a promising long-term solution, yet its commercialisation faces a fundamental paradox in today’s investment environment: pilot plants are essential to de-risk physics, engineering, and operations, but their limited lifetime energy output and high upfront costs make them difficult to finance. This paper presents Tokamak Energy’s response: ST-E1, a pre-concept design for a low-aspect-ratio tokamak power plant engineered specifically to overcome this challenge. ST-E1 is designed from the outset for phased operation—pilot and commercial phases, with an upgrade phase in between—with emphasis on commercial viability, maintainability, nuclear engineering, modularity, and upgradability. A key design principle is the deliberate separation of long-lived assets, such as the magnet cage and vacuum vessel, from replaceable in-vessel systems. This provides an attractive and credible investment approach to generate operational data and de-risk key technologies while preserving most capital-intensive assets for later commercial phases. The architecture supports continuous optimisation toward high net electric power (targeting 800–1000 MW net electric), a normalised capital expenditure of $\$$ 12–14k/kW of net electric power, and high availability (targeting > 80%). A tokamak core with a 5 m major radius, aspect ratio of 2.3, and on-plasma axis toroidal field of 5.25 T was selected to meet these objectives. This paper summarises the ST-E1 design philosophy, principal features, and development methodology. It introduces a Focus Collection of 11 papers detailing the pre-concept design of the entire tokamak and corresponding plant.

ST-E1↗
DOE OSTI2022

Quantifying the regional stranded asset risks from new coal plants under 1.5 °C

Momentum to phase out unabated coal use is growing globally. This transition is critical to meeting the Paris climate goals but can potentially lead to large amounts of stranded assets, especially in regions with newer and growing coal fleets. Here we combine plant-level data with a global integrated assessment model to quantify changes in global stranded asset risks from coal-fired power plants across regions and over time. With new plant proposals, cancellations, and retirements over the past five years, global net committed emissions in 2030 from existing and planned coal plants declined by 3.3 GtCO 2 (25%). While these emissions are now roughly in line with initial Nationally Determined Contributions (NDCs) to the Paris Agreement, they remain far off track from longer-term climate goals. Progress made in 2021 towards no new coal can potentially avoid a 24% (503 GW) increase in capacity and a 55% ($520 billion) increase in stranded assets under 1.5 °C. Stranded asset risks fall disproportionately on emerging Asian economies with newer and growing coal fleets. Recent no new coal commitments from major coal financers can potentially reduce stranding of international investments by over 50%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Careers at National Laboratories

It’s common for math majors and professors to be aware of possible careers outside of teaching, especially jobs like data science, finance, actuarial science, and some government agencies. But from my experience talking with undergraduates, graduate students, and professors in mathematics, careers at national laboratories are not as well-known. It’s my goal in this article to give you some background and history of the national lab system, a glimpse into the work mathematicians do, and finally some insight into getting a job at a national lab.

career development, recruitment↗
DOE OSTI2015

Adapting California's Ecosystems to a Changing Climate

Significant efforts are underway to translate improved understanding of how climate change is altering ecosystems into practical actions for sustaining ecosystem functions and benefits. We explore this transition in California, where adaptation and mitigation are advancing relatively rapidly, through four case studies that span large spatial domains and encompass diverse ecological systems, institutions, ownerships, and policies. The case studies demonstrate the context specificity of societal efforts to adapt ecosystems to climate change and involve applications of diverse scientific tools (e.g., scenario analyses, downscaled climate projections, ecological and connectivity models) tailored to specific planning and management situations (alternative energy siting, wetland management, rangeland management, open space planning). Here, they illustrate how existing institutional and policy frameworks provide numerous opportunities to advance adaptation related to ecosystems and suggest that progress is likely to be greatest when scientific knowledge is integrated into collective planning and when supportive policies and financing enable action.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗
DOE OSTI2025

Classical optimization with imaginary-time block encoding on quantum computers: The MaxCut problem

Optimization problems in finance, physics, and computer science are typically very hard to tackle in classical computing; quantum computing could help speed up computations and provide efficient methods for tackling large problems. Typically, to treat a problem with a quantum computer, the optimal solution is cast as the ground state of a diagonal Hamiltonian. Here, we develop a method, called imaginary-time evolution block encoding (ITE-BE), based on a recent imaginary-time algorithm, which requires no variational parameter optimization, as all parameters can be derived analytically from the target Hamiltonian. We also demonstrate that our method can be successfully combined with other quantum algorithms such as the quantum approximate optimization algorithm (QAOA). For illustration, here we study the MaxCut problem. We find that the QAOA ansatz increases the postselection success of ITE-BE, and shallow QAOA circuits, when boosted with ITE-BE, achieve better performance than deeper QAOA circuits. For the special case of the transverse initial state, we adapt our block-encoding scheme to allow for a deterministic application of the first layer of the circuit.

Zhong, Dawei [University of Southern California, L↗
DOE OSTI2014

Modeling the irradiance and temperature dependence of photovoltaic modules in PVsyst

In order to reliably simulate the energy yield of photovoltaic (PV) systems, it is necessary to have an accurate model of how the PV modules perform with respect to irradiance and cell temperature. Building on previous work that addresses the irradiance dependence, two approaches to fit the temperature dependence of module power in PVsyst have been developed and are applied here to recent multi-irradiance and -temperature data for a standard Yingli Solar PV module type. The results demonstrate that it is possible to match the measured irradiance and temperature dependence of PV modules in PVsyst. As a result, improvements in energy yield prediction using the optimized models relative to the PVsyst standard model are considered significant for decisions about project financing.

14 SOLAR ENERGY↗
DOE OSTI2018

Consumer Applications of Quantum Computing: A Promising Approach for Secure Computation, Trusted Data Storage, and Efficient Applications

Demands from the commerce, finance, security, and logistics sectors drive the persistent growth of computing. As current research focuses on providing new computing capabilities using disruptive approaches, quantum computing represents a promising strategy that offers new capabilities in secure computation, trusted data storage, and efficient applications. Here, this article discusses the growing awareness that quantum computing can impact a broad variety of consumer concerns and applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Understanding Inter-Annual Variability of PV Energy Production in the Contiguous United States

Year-to-year variability of photovoltaic (PV) generation is an important factor for project financing as well as for modeling the reliability and resource adequacy of power systems. In this work, we analyze inter-annual variability of PV generation across the contiguous United States using the National Solar Radiation Database (NSRDB) from 1998 to 2014. We compare the estimated PV generation from the typical meteorological year (TMY) against the long-term mean, and find that on average the TMY tends to overpredict estimated PV production. However, we also found significant regional bias and spatial clustering in that comparison, such that there are many regional pockets of underprediction as well. Finally, we show that there is not a single year of data that most closely approximates a representative 'resource year' for all regions of the United States. These results point to the need to understand inter-annual variability at individual sites and to be aware of the shortcomings of using TMY or a single year of data for project or grid modeling.

14 SOLAR ENERGY↗
DOE OSTI2016

Shortwave Radiometer Calibration Methods Comparison and Resulting Solar Irradiance Measurement Differences: A User Perspective

Banks financing solar energy projects require assurance that these systems will produce the energy predicted. Furthermore, utility planners and grid system operators need to understand the impact of the variable solar resource on solar energy conversion system performance. Accurate solar radiation data sets reduce the expense associated with mitigating performance risk and assist in understanding the impacts of solar resource variability. The accuracy of solar radiation measured by radiometers depends on the instrument performance specification, installation method, calibration procedure, measurement conditions, maintenance practices, location, and environmental conditions. This study addresses the effect of different calibration methods provided by radiometric calibration service providers, such as NREL and manufacturers of radiometers, on the resulting calibration responsivity. Some of these radiometers are calibrated indoors and some outdoors. To establish or understand the differences in calibration methodology, we processed and analyzed field-measured data from these radiometers. This study investigates calibration responsivities provided by NREL's broadband outdoor radiometer calibration (BORCAL) and a few prominent manufacturers. The BORCAL method provides the outdoor calibration responsivity of pyranometers and pyrheliometers at 45 degree solar zenith angle, and as a function of solar zenith angle determined by clear-sky comparisons with reference irradiance. The BORCAL method also employs a thermal offset correction to the calibration responsivity of single-black thermopile detectors used in pyranometers. Indoor calibrations of radiometers by their manufacturers are performed using a stable artificial light source in a side-by-side comparison between the test radiometer under calibration and a reference radiometer of the same type. In both methods, the reference radiometer calibrations are traceable to the World Radiometric Reference (WRR). These different methods of calibration demonstrated +1% to +2% differences in solar irradiance measurement. Analyzing these differences will ultimately help determine the uncertainty of the field radiometer data and guide the development of a consensus standard for calibration. Further advancing procedures for precisely calibrating radiometers to world reference standards that reduce measurement uncertainty will allow more accurate prediction of solar output and improve the bankability of solar projects.

14 SOLAR ENERGY↗
DOE OSTI2016

Module Degradation Mechanisms Studied by a Multi-Scale Approach

A key pathway to meeting the Department of Energy SunShot 2020 goals is to reduce financing costs by improving investor confidence through improved photovoltaic (PV) module reliability. A comprehensive approach to further understand and improve PV reliability includes characterization techniques and modeling from module to atomic scale. Imaging techniques, which include photoluminescence, electroluminescence, and lock-in thermography, are used to locate localized defects responsible for module degradation. Small area samples containing such defects are prepared using coring techniques and are then suitable and available for microscopic study and specific defect modeling and analysis.

14 SOLAR ENERGY↗
DOE OSTI2018

Quantifying Year-to-Year Variations in Solar Panel Soiling from PV Energy-Production Data

We present a method for quantifying solar panel soiling loss from PV energy-production data and show how it can be used to quantify year-to-year variations in soiling loss. Cleaning events are automatically detected, eliminating the need for precipitation data or assumptions about cleaning. The method also calculates the reduction of energy yield due to soiling, not just a soiling rate. We apply the method annually and also to multi-year datasets. We find significant year-to-year variation in soiling loss, a result with important implications for site planning and financing. The method presented here can leverage existing datasets of daily energy yield to quantify annual and total soiling risk without the need for new hardware and serves as a supplement to standard plant planning practices.

14 SOLAR ENERGY↗
DOE OSTI2025

ReVise: A Human-AI Interface for Incremental Algorithmic Recourse

The recent adoption of artificial intelligence in socio-technical systems raises concerns about the black-box nature of the resulting decisions in fields such as hiring, finance, admissions, etc. If data subjects—such as job applicants, loan applicants, and students—receive an unfavorable outcome, they may be interested in algorithmic recourse, which involves updating certain features to yield a more favorable result when re-evaluated by algorithmic decision-making. Unfortunately, when individuals do not fully understand the incremental steps needed to change their circumstances, they risk following misguided paths that can lead to significant, long-term adverse consequences. Existing recourse approaches focus exclusively on the final recourse goal but neglect the possible incremental steps to reach the goal with real-life constraints, user preferences, and model artifacts. To address this gap, we formulate a visual analytic workflow for incremental recourse planning in collaboration with AI/ML experts and contribute an interactive visualization interface that helps data subjects efficiently navigate the recourse alternatives and make an informed decision. We also present one of the many usage scenarios, developed during exploratory feedback sessions with twelve graduate students using a real-world dataset, which demonstrates that our approach can be instrumental for data subjects in choosing a suitable recourse path.

algorithmic recourse↗