Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “capital”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31

A Methodology to Support the Development of a New State Vision for the U.S. Nuclear Industry

Recent changes in natural gas prices combined with reduced capital costs for solar and wind systems has created challenges for the continued operation of existing nuclear power plants (NPPs) in the United States. A new strategy in the way in which U.S. NPPs are operated, maintained, and supported is needed. One such strategy is to transform the NPP operating model through a business-driven approach that leverages technology to enable new capabilities that improve performance and reduce costs. This paper presents a methodology for developing an achievable yet transformative new state vision that ensures the continued safe and efficient operations of the U.S. NPP fleet. Here this work builds on existing guidance and leverages previous research to comprehensively address both utility needs and high-level human factors engineering design principles when developing a new state vision. The proposed methodology is intended to provide industry-wide guidance for developing a new state vision that leverages both the selected vendor’s capabilities in a way that meets the utility’s modernization goals while ensuring state-of-the-art systems engineering and human factors engineering principles are applied that promote overall plant safety, performance, and efficiency.

99 GENERAL AND MISCELLANEOUS↗

Large-scale Multiphysics Simulations of Small Modular Reactors Operating in Natural Circulation

Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. In conclusion, the results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.

ECP↗

Preliminary Neutronics Design and Analysis of the Fast Modular Reactor

General Atomics is developing a new 100-MW(thermal) fast modular reactor (FMR) that provides safe, carbon-free electricity and is capable of incremental capacity additions. The modular design allows it to be factory built and assembled onsite to keep the capital cost low, while the use of dry cooling facilitates siting to complement renewables in nearly any location. The FMR uses high-assay low-enriched uranium-dioxide fuel encapsulated by recognized irradiationresistant silicon carbide composite (SiGA®) cladding that is derisked in the current accident-tolerant fuel program. The FMR fuel assembly is a hexagonal fuel bundle of 120 fuel rods. The total length of the fuel assembly is less than 4 m, with an active fuel length of 1.8 m. The fuel assemblies are configured in an annular core that is located and supported by the reactor internals. The coolant material is helium at a normal operating pressure of 7 MPa. The core is surrounded by zirconium silicide (Zr 3 Si 2 ) and graphite reflector blocks. The fuel, coolant, internals, and reflectors are contained within a reactor pressure vessel. Here, the preliminary nuclear design and analysis established the arrangement of the active core and reflector blocks. The nuclear design analyses of the FMR defined the design parameters, such as fuel enrichments, excess reactivity, fueling scheme, fuel cycle, power distribution, and control rod worth. The preliminary conceptual design determined the three-batch fueling scheme with the allowable total power peaking factor of 1.5. The average discharge burnup is 100 GW days per ton of uranium.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Popnet : computer vision based deep learning model for forecasting gridded population

Here, this study introduces Popnet, a deep learning model for forecasting 1 km-gridded populations, integrating U-Net, ConvLSTM, a Spatial Autocorrelation module and deep ensemble methods. Using spatial variables and population data from 2000 to 2020, Popnet predicts South Korea’s population trends by age groups (under 14, 15-64 and over 65) up to 2040. In validation, it outperforms traditional machine learning and state-of-the-art computer vision models. The output of this model discovered significant polarisation: population growth in urban areas, especially the capital region, and severe depopulation in rural areas. Popnet is a robust tool for offering significant insights to policymakers and related stakeholders about the detailed future population, which allows them to establish detailed, localised planning and resource allocations.

computer vision↗

Regional Economic Impacts of the Los Angeles 100% Renewable Energy Transition

To help mitigate greenhouse gas (GHGs) generation from burning fossil fuels, many state and local governments are requiring utilities to dramatically increase the share of electricity generated from renewable sources. The City of Los Angeles has set a target of 100% renewable energy by 2045 and has formulated a plan that considers nine potential alternative scenarios that differ by technology, location, and timing. Each scenario has a unique set of local investments, operating and maintenance (O&M) costs, and concomitant rate structures. In this study we develop and apply a computable general equilibrium (CGE) model built specifically for LA to estimate and compare the economic impacts for each of the scenarios over time relative to a reference case. We find differences in economic impacts across scenarios, depending on the level and timing of investment and O&M expenditures, as well as differences in the relative rate changes across scenarios. Results show that employment and economic output are positively correlated with greater capital and O&M spending, while higher electricity rates can dampen economic activity. Several scenarios generate positive economic impacts relative to the reference case, showing that the transition need not have harmful economic impacts, and all scenarios generate a number of other positive co-benefits, such as reduced damage to health from the reduction of ordinary air pollutants. The net employment impacts from 2026 to 2045 across the scenarios range from a low of 3,600 job-year losses annually to 4,700 job-year gains, both around only 0.1% of the baseline average annual employment in the city over that period. The analysis also indicates that lower-income households are relatively more affected than others by the scenarios. Overall, even in the most negatively impactful case, the economic output and employment effects are quite small when taken in the context of the overall size of the regional economy and the large reduction in GHGs.

economic impact modeling↗

Integrating Spatial and Ethnographic Methods for Resilience Research: A Thick Mapping Approach for Hurricane Maria in Puerto Rico

Hurricane Maria left unprecedented impacts on Puerto Rican communities, leaving some without infrastructure services and unable to communicate with family for several months. Here, to understand the forms of community-level resilience that emerged while hard infrastructure systems took time recover, this article (1) abductively explores resilience as an emergent phenomenon of complex adaptive systems; (2) identifies subsequent forms of social capital, local adaptive capacities, and manifestations of quantifiable variables, such as infrastructure performance, in community experiences; and (3) demonstrates a framework to integrate disparate methodologies for resilience assessments via a multiplicity of mappings of space and place. We combine ethnographic and geospatial methods into an interactive GeoApp for analysis using participant-coded narratives and a series of geospatial indicators as a thick map. Thick mapping facilitates quantitative and qualitative data analysis at several scales, while enabling qualitative query of collected narratives. Results highlight local innovation, community bonding and bridging, and nuances in the role of public institutions as emergent elements of resilience. The thick map shows how top-down assessments can be augmented by thick data and how multiple framings can be anchored in the same system or place. These findings are important to inform and integrate community-oriented and technocentric solutions toward resilience-enhancing measures.

54 ENVIRONMENTAL SCIENCES↗

Demonstration of $E$ acc = 10 MV m −1 with Nb 3 Sn cavities in a cryomodule

Accelerating cryomodules with superconducting cavities are key components for particle accelerators. The efficiency, energy gain and operating temperature of cavities drive the operating and capital costs; hence, advances in these areas enable future accelerators. While superconducting cavities are currently made from Nb, Nb 3 Sn, with a superconducting transition temperature and superheating field approximately twice that of Nb, is poised to substantially improve the efficiency and energy gain. We present results from the first cryomodule with two five-cell 1.5 GHz superconducting radiofrequency Nb cavities coated with Nb 3 Sn, which attained an accelerating gradient of ⩾10 MV m −1 with low cryogenic loss at 4.4 K.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Fusion by beam ions in a low collisionality, high mirror ratio magnetic mirror

Abstract The classical problem of neutral beam ions slowing down in a magnetic mirror geometry is revisited to provide predictive capability for the new Wisconsin HTS Axisymmetric Mirror under development at the University of Wisconsin. A Fokker–Planck model named fast beam ion solver (FBIS) is developed to include the spatial non-uniformity of a physical mirror geometry. The mathematical framework allows for efficient orbit averaging of the pitch-angle scattering operator, and permits a determination of the axial profile of the ambipolar potential confining the electrons. The numerical results from FBIS are consistent with earlier work, but further show how mirror-ratio and a near square magnetic well optimizes the fusion gain. The numerical results are also applied to inform the conceptual design of WHAM++, a low capital-cost breakeven-class magnetic mirror device.

Egedal, J. (ORCID:0000000177531529)↗

Exploring the fusion power plant design space: comparative analysis of positive and negative triangularity tokamaks through optimization

The optimal configuration choice between positive triangularity (PT) and negative triangularity (NT) tokamaks for fusion power plants hinges on navigating different operational constraints rather than achieving specific plasma performance metrics. This study presents a systematic comparison using constrained multi-objective optimization with the integrated FUsion Synthesis Engine (FUSE) framework. Over 200 000 integrated design evaluations were performed exploring the trade-offs between capital cost minimization and operational reliability (maximizing q 95 ) while satisfying engineering constraints including 250 ± 50 MW net electric power, tritium breeding ratio > 1.1, power exhaust limits and an hour flattop time. Both configurations achieve similar cost-performance Pareto fronts through contrasting design philosophies. PT, while demonstrating resilience to pedestal degradation (compensating for up to 40% reduction), are constrained to larger machines (R 0 > 6.5 m) by the narrow operational window between L–H threshold requirements and the research-established power exhaust limit (P sol /R < 15 MW m –1 ). This forces optimization through comparatively reduced magnetic field (∼8 T). NT configurations exploit their freedom from these constraints to access compact, high-field designs (R 0 ~ 5.5 m, B 0 >12 T), creating natural synergy with advancing HTS technology. Sensitivity analyses reveal that PT’s economic viability depends critically on uncertainties in L–H threshold scaling and power handling limits. Notably, a 50% variation in either could eliminate viable designs or enable access to the compact design space. These results suggest configuration selection should be risk-informed: PT offers the lowest-cost path when operational constraints can be confidently predicted, while NT is robust to large variations in constraints and physics uncertainties.

FUSE framework↗

Physics basis for the reference flat-top plasma scenario in the ST–E1 fusion power plant

As part of the U.S. Department of Energy’s Milestone-Based Fusion Energy Development Program, Tokamak Energy has completed the pre-concept design of the ST–E1 fusion power plant. ST–E1 is envisaged to operate in two phases: a pilot plant phase, targeting sustained net power production of 300 - 500 MWe for a duration >1 hr, followed by a commercial power plant phase targeting steady-state operations and a normalised overnight capital cost of ⩽12 000 $\$$/kWe. The design process adopted was highly iterative, integrating all major plant systems and progressing in a phased fidelity approach. At the pre-conceptual stage, the emphasis has been on exploring the design space, identifying the main system-level trade-offs, and making the key decisions that define the overall plant concept, rather than optimising a single operating point. This paper, part of a focused collection detailing the ST–E1 pre-concept design, addresses the development of a series of reference flat-top plasma operating points for the pilot plant phase. A modelling workflow was established to develop and assess candidate plasma design points and explore key dependencies. The workflow includes integrated core plasma modelling, magnetohydrodynamic (MHD) stability assessment, equilibrium generation, scrape-off-layer and exhaust modelling, heating & current drive design and optimisation, and turbulent transport modelling. Using this framework, the impact of several key parameters on the flat-top operating space was investigated, including the density limit, core radiation fraction and divertor power loading, level of external heating and curent drive power and assumed pedestal characteristics. The MHD stability, controllability and micro-stability characteristics of these plasmas were also analysed. These investigations informed the definition of a set of fully non-inductive, flat-top reference operating points that satisfy the high-level ST–E1 mission, including a low and high density case, a case that is stable to resistive wall modes and a case with reduced divertor power loading.

ST–E1↗

Process-based balance of system cost modeling for offshore wind power plants in the United States

This paper describes the development of a process-based and open-source balance of system cost model that provides the capability to evaluate both existing and novel offshore wind technologies. Individual design and installation steps are represented with bottom-up engineering models that compute times and costs associated with the process; furthermore, operational constraints are assigned to each process so that delays caused by weather and presence of marine mammals may be accounted for in the overall project timeline. The model structure, assumptions, inputs, and results are vetted with industry partners and compared against actual projects for validation. Installation times show reasonable agreement with real data. Project cost sensitivities are investigated to compute the system-level impact of different design choices. First, individual vessel efficiencies are computed for varying numbers of installation vessels and weather time series to show the diminishing returns of more than two feeder barges. Then, array cable capital costs and installation times are determined for a representative project with different turbine sizes. These values quantify the cost-benefit tradeoffs and show a net-cost savings of decreasing numbers of turbines, increased turbine spacing, and fewer turbine terminations. These results demonstrate that the balance of system model features the accuracy, functionality, and accessibility to serve as the foundation for a wide range of analyses to identify cost reduction potentials for offshore wind energy in the United States.

17 WIND ENERGY↗

IEA Wind Task 32 and Task 37: Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering

Lidar-assisted control is a promising technology for reducing the levelized cost of energy from wind turbines, but quantifying its impact at the overall system level requires sophisticated systems engineering analysis and optimization frameworks. The joint workshop on Optimizing Wind Turbines with Lidar-Assisted Control Using Systems Engineering was held by the International Energy Agency Wind Task 32 (Lidar) and Task 37 (Systems Engineering) in October 2019 to address this challenge. This paper summarizes the outcome of the workshop and presents a road map for further research. The most promising applications of lidar-assisted control identified at the workshop and discussed here include 1) increasing annual energy production, 2) decreasing capital expenditure costs by reducing design loads, 3) extending turbine lifetime by reducing operating loads, and 4) enabling wind turbine class upgrades. For each application, we review the state of the art and highlight remaining research needs. Finally, we discuss strategies for addressing these research needs by conducting high-fidelity systems engineering optimizations.

17 WIND ENERGY↗

Development of an open-source segmented blade design tool

As wind turbines continue to grow ever larger to reduce the cost of energy, their blades follow suit, with the largest commercial offshore blades extending past 100 m. Massive blades such as these raise key transportation and manufacturing challenges, especially for land-based turbines. Segmented blades are one solution and are garnering increased industry and research interest. In this work, a detailed mechanical joint model is integrated into the Wind-Plant Integrated System Design and Engineering Model (WISDEM ® ), which will facilitate future segmented blade research and optimization. WISDEM is used to design a wind turbine with 100-m segmented blades. This wind turbine design is compared to other machines with 100-m monolithic blades designed for rail-transportability. The designs are compared in terms of blade mass and cost, turbine capital cost, annual energy production, and levelized cost of energy, with monolithic designs being the lightest and most economical. However, this result may vary by wind plant location. A variety of segmentation joint types exist, and they will inevitably vary in parameters such as cost, spanwise location, and physical characteristics. This work examines the sensitivity of wind turbine design drivers and annual energy production to a variety of the aforementioned parameters, using the open-source wind turbine design codes OpenFAST and WISDEM, finding that joint mass, stiffness, and location can have significant effects on design drivers.

17 WIND ENERGY↗

Challenges and Possible Solutions in Aeroelastic Modeling for the Distributed Wind Industry

Aeroelastic modeling (AM) is the primary methodology for structural and performance assessment of any wind turbine; it provides an understanding of the impact of design parameters on turbine loading and power response before witnessing it in the field. Despite these advantages, the use of AM in the distributed wind technology (DWT) sector is limited. This article represents a short summary of an in-depth assessment by the authors of the status of AM and its role within the distributed wind technology design standards. The research gathered input and feedback from a large number of U.S. and international stakeholders, reviewed technical strengths and weaknesses of the current edition of the design standards, analyzed the minutes from recent industry workshops and meetings, collected publicly available AM templates, and provided an evaluation of the existing AM codes. Several goals were achieved including providing strategies for the load assessment categorization of turbines based on rotor swept area and archetype, and guidance for AM verification and validation. Recommendations within this study will advance the value and the ease-of-use of AM, thereby allowing the industry to better capitalize this underutilized tool, resulting in a more efficient design process, an easier path to certification, and overall better and more reliable distributed wind technology products.

17 WIND ENERGY↗

Progress toward Accelogic compression in ROOT

For the last 7 years, Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom-line outcome will be to provide state-of-the-art compression algorithms --and accompanying software libraries-- able to surpass the performance of the compression engines currently available in the ROOT [7] framework. The resulting technology has the capability to enable substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4 [6].As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility.In this contribution, we will present our efforts integrating our concepts of “functionally lossless compression” within the ROOT framework implementation, with the purpose of producing a basic solution readily integrated into HENP applications. We will also present our progress applying this compression through realistic examples of analysis from both the STAR and CMS experiments.

Canal, Ph.↗

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

17 WIND ENERGY↗

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗

Stranded asset implications of the Paris Agreement in Latin America and the Caribbean

Achieving the Paris Agreement's near-term goals (Nationally Determined Contributions, NDCs) and long-term temperature targets could result in pre-mature retirement, or stranding, of carbon-intensive assets before the end of their useful lifetime. We use an integrated assessment model to quantify the implications of the Paris Agreement for stranded assets in Latin America and the Caribbean (LAC), a developing region with the least carbon-intensive power sector in the world. We find that meeting the Paris goals results in stranding of 37-90 billion and investment of 1.9-2.6 trillion worth of power sector capital (2021-2050) across a range of future scenarios. Strengthening the NDCs could reduce stranding costs by 27-40%. Additionally, while politically shielding power plants from pre-mature retirement or increasing the role of other sectors (e.g. land-use) could also reduce power sector stranding, such actions could make mitigation more expensive and negatively impact society. For example, we find that avoiding stranded assets in the power sector increases food prices 13%, suggesting implications for food security in LAC. Our analysis demonstrates that climate goals are relevant for investment decisions even in developing countries with low emissions.

54 ENVIRONMENTAL SCIENCES↗