Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Power Development”

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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Novel High Temperature Carbide and Boride Ceramics for Direct Power Extraction Electrode Applications. Final report

The current project aims to develop new carbide and boride ceramic materials that incorporate different metal elements (e.g., (Hf 1-x Zr x )B 2 , also called ceramic solid solutions) and understand the fundamental composition-processing-structure-property relationships for such materials. Specifically, nano powders and related nano-composites for selected mixed metal carbide and boride materials are synthesized from nano-scale mixed precursors obtained from solution-based processing via heat treatment in inert atmosphere. The obtained fine powders were then consolidated into dense ceramics via a novel flash sintering process. The mechanical properties and thermal oxidation resistance for the obtained materials were evaluated for these materials. It was found that different synthesis routes produced powders with somewhat different characteristics in terms of composition and microstructure, which then led to different properties for the final ceramics. The synthesis and processing methods demonstrated in this study might be adopted for developing other similar high temperature ceramics, while the mixed metal or solid solution ceramic materials obtained from this study might be used as hot electrodes for direction power extraction and other energy-related applications.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Colloidal Quantum Dot Solar Cells: Progressive Deposition Techniques and Future Prospects on Large-area Fabrication

Colloidally grown nanosized semiconductors yield extremely high-quality optoelectronic materials. Many examples have pointed to near perfect photoluminescence quantum yields, meaning non-radiative optical processes (losses) can be completely suppressed allowing for technology-leading materials as high purity color centers in display technology and emitters in LEDs. Furthermore, because of high chemical yield, and improved understanding of the surfaces, these materials, particularly colloidal quantum dots (QDs) can also be ideal candidates for other optoelectronic applications. Given the strong drive toward carbon neutrality and limiting climate change, electricity from solar photovoltaics will play a large role in the power generation sector. QDs have been developed and shown dramatic improvements over the past 15 years as photoactive materials in photovoltaics and have unique potential with various innovative deposition properties which could lead to exceptionally low-cost and high-performance devices. Once the key issues related to charge transport in optically thick arrays are addressed, QD-based photovoltaic technology could become a better candidate for practical application. In this article, w e show how the possibilities of different deposition techniques could bring QD-based solar cells to the industrial level and discuss the challenges for perovskite QD solar cells in particular, to achieve large-area fabrication for further advancing technology to solve pivotal energy and environmental issues.

14 SOLAR ENERGY↗
DOE OSTI2021

An uncertainty quantification method relevant to material test reactors

Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. Furthermore, the two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Cooperative fault management for resilient integration of renewable energy

Cooperative fault management (CFM) is designed herein to control different types of renewable energy resources cooperatively during electrical faults. This paper studies systems with a high penetration of photovoltaic (PV) energy and wind energy. First, CFM leverages power converters of PV farms to boost the ride-through capability of nearby doubly-fed induction generators (DFIGs). By controlling PV farms’ output voltages to change smoothly during both fault initiation and fault clearance, the widely used crowbar in DFIGs is less likely to be activated. Crowbar activation adversely makes DFIGs lose controllability and absorb reactive power. The second contribution is the development of a software-defined CFM controller and a controller in-the-loop demonstration of the real-time performance of this optimization-based CFM. CFM capitalizes on distributed optimization formulation to enable flexibility, plug-and-play, and privacy-preserving. Computation time, however, is a major concern for optimization-based dynamics control. Here, real-time controller-in-the-loop simulation results show optimization-based CFM can output reference values around 60 ms and is quick enough for dynamic control.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Comprehensive framework for data-driven model form discovery of the closure laws in thermal-hydraulics codes

The two-phase two-fluid model is a basis of many thermal-hydraulics codes used in design, licensing, and safety considerations of nuclear power plants. Thermal-hydraulics codes rely on the closure laws to close the system of conservation equations and describe the interactions between phases. These laws, derived from years of experimental investigations, are semi-empirical correlations that lack generality and have a limited range of applicability. Increase of computational power, availability of new experiments, and development of high-fidelity simulations has increased the number of validation data. The discrepancies between the code predictions and the validation data are a great source of knowledge. Missing physics that are not included in the model but are important for the considered phenomena can be discovered by propagating the information from the experimental results through the model. Furthermore, physics-discovered data-driven model form (P3DM) methodology integrates available integral effect tests and separate effects tests to determine the necessary corrections to the model form of the closure laws. In contrast to existing calibration techniques, the methodology modifies the functional form of the closure laws. Based on the functional form of the correction, the missing physics that were not included in the original model can be discovered. The methodology provides the alternative to the machine learning approach, in which the model is discovered in the form of the intractable black-box relation. In this work, the methodology was applied to the CTF subchannel code to improve the prediction of the two-phase flow phenomena.

42 ENGINEERING↗
DOE OSTI2024

Wave-powered water pump for upwelling in aquaculture: Numerical model and ocean test

Wave-powered upwelling can increase the productivity and survivability of several aquaculture species. This enhancement is due to transporting cold, nutrient-rich ocean water, typically found lower in the water column, to the surface. Macroalgaes, like kelp, exhibit increased growth from these altered conditions. The University of New Hampshire’s (UNH) wave-powered water pump (wave pump) is a point absorber wave energy converter (WEC) that uses ocean waves to create relative motion between a spar buoy and a concentric float which drives an internal pump. A numerical model of the wave pump was developed using WEC-Sim to predict device performance in the ocean. Wave pump performance was evaluated during a five day ocean test near Appledore Island in Maine in March 2023, where volumetric flow rate, relative distance between spar and float, and wave conditions were measured. These data were then used for numerical model validation. The ocean deployment recorded the device’s performance in a variety of sea states, with average significant wave heights up to 0.7 m. The ocean test data were compared to the WEC-Sim numerical model of the device with favorable results. Average values of device stroke period, stroke height, and flow rate agreed between the ocean test and model data to within approximately 16 to 22%. Furthermore, the validated numerical model provides a valuable tool for improving the design and developing a commercial-scale, wave-powered water pump for use in aquaculture.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Costs of mitigating the environmental impacts of hydropower projects in the United States

Developers are required to mitigate the environmental impacts of hydropower projects in the United States (U.S.) but there is very little accessible information on the associated costs. This work compiles and analyses a dataset of environmental impacts mitigation costs for 182 hydropower projects based on documents obtained from the U.S. Federal Energy Regulatory Commission (FERC). The analysis shows that environmental costs vary wildly across hydropower project classes and mitigation measures, even when normalized by plant capacity. Capital costs per kilowatt are generally higher for relicensed conventional hydropower plants, and lower for new and relicensed pumped storage hydropower plants, relative to other project classes. Smaller plants tend to spend a higher share of total project costs on mitigating environmental impacts than larger plants, and measures related to Aquatic Species, Project Operations, and Recreation have the highest capital cost per kilowatt. These findings mean that environmental costs could become a key decision variable for new hydropower developments in the U.S. due to the small scale of most of the remaining potential and the increasing stringency of environmental requirements. Therefore, technologies to reduce the environmental impacts and costs of hydropower would be important for future project developments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An efficient method to identify uncertainties of WRF-Solar variables in forecasting solar irradiance using a tangent linear sensitivity analysis

Uncertainty in predicting solar energy resources introduces major challenges in power system management and necessitates the development of reliable probabilistic solar forecasts. As the first part of the development of probabilistic forecasts based on the Weather Research and Forecasting model with solar extensions (WRF-Solar), this study presents a tangent linear approach to identify input variables responsible for the largest uncertainties in predicting surface solar irradiance and clouds. A tangent linear analysis is capable of efficiently investigating sensitivities of output variables with respect to various input variables of WRF-Solar because this approach avoids the computational burden of perturbing the initial conditions of individual input variables. We develop tangent linear models (TLMs) for six WRF-Solar physics packages that control the formation and dissipation of clouds and solar radiation, and we evaluate the validity of TLMs using a linearity test. The tangent linear sensitivity analysis is conducted under various scenarios based on satellite observations and model simulations to consider realistic input conditions. A simple method is used to quantify the impact of the uncertainty of input variables on the output variables from the TLMs. The results demonstrate that uncertainties in the output variables that are the focus of this study—including global horizontal irradiance, direct normal irradiance, cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes—are highly sensitive to uncertainties in 14 input variables. This study indicates that the tangent linear method can identify key variables of physics modules in WRF-Solar that can be stochastically perturbed to generate ensemble-based probabilistic forecasts.

14 SOLAR ENERGY↗
DOE OSTI2021

Characteristics of Non-Fullerene Acceptor-Based Organic Photovoltaic Active Layers Using X-ray Scattering and Solid-State NMR

With the recent development of non-fullerene acceptors, power conversion efficiencies of bulk-heterojunction organic solar cells have exceeded 18%. The morphology of the BHJ active layer, including packing, ordering, orientation, and phase behavior of the donor(s) and acceptor(s), plays critical roles in determining the device performance. We characterized the morphology of active layers consisting of mixtures of a PTB7/PTB7-Th (donor) and ITIC (acceptor) using grazing incidence wide-angle X-ray scattering, resonant soft X-ray scattering, and solid-state nuclear magnetic resonance (ssNMR) to correlate the morphology with device performance. PTB7-Th/ITIC shows a better device performance than that of PTB7/ITIC due to a smaller π-πstacking distance and smaller domain size of the phase separated morphology. One of PTB7/ITIC samples, processed from mixed solvents (chlorobenzene/benzene = 1:1 by volume), shows a possible partial miscibility and smaller domain size as revealed by ssNMR T 1ρ relaxation times, which is detrimental to device performance. ssNMR results showed that ITIC could crystallize into different forms depending on processing conditions, which may have implications on the manufacturing of devices using it as an ingredient, as well as its long-term stability in service.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exceptional Electrical Detection of Trace NO 2 via Mixed Metal MOF-on-MOF Film-Based Sensors

The tunability of metal–organic frameworks (MOFs) makes them exceptional materials for the development of highly selective, low-power sensors for toxic gas detection. Herein, we demonstrate enhanced detection of NO 2 gas by a MOF-based electrical impedance sensor made using a unique mixed metal MOF-on-MOF synthesis. For this work, a combined experimental and computational study was performed using the exemplar Ni x Mg 1–x -MOF-74 to understand the fundamental structure–property relationships behind metal mixing and MOF film synthesis methods on sensor performance. Density functional theory results indicated that the presence of Ni in Mg-MOF-74 increased framework stability and increased the electron density of states at lower energies near the HOMO, as well as enhanced the NO 2 –Mg adsorption interaction. Impedance data of the Ni x Mg 1–x -MOF-74 films with larger Ni contents showed greater impedance change after exposure to 1 ppm of NO 2 gas. Furthermore, when synthesized through either a drop-cast or direct solvothermal film growth approach, the monometallic Ni-based sensors had the best performance. However, the mixed metal Ni x Mg 1–x -MOF-74 sensors synthesized through a MOF-on-MOF approach resulted in the highest impedance change, outperforming all monometallic Ni-based sensors. In particular, the mixed metal Ni-on-Mg-MOF-74 film was the best-performing sensor with an impedance change of 309 upon trace NO 2 exposure. Change in impedance response after NO 2 exposure was improved by 52% compared to the best monometallic Ni-on-Ni-MOF-74 sensor. Structural analysis of the Ni-on-Mg film showed that the first Mg-MOF-74 layer acts as a structural template controlling the structural features of the final film after metal exchange with Ni. This led to improved film quality, evidenced by the greater crystallinity and larger MOF grain sizes, and resulted in enhanced sensor performance which was not achievable through other metal mixing methods. Altogether, this study identifies structure–property relationships and synthetic templating methods that inform MOF-based sensor design, allowing for improved detection of toxic compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Gate control of electron correlations towards Mott field effect transistors (MottFET)

The modulation of channel conductance in field-effect transistors (FETs) via metal-insulator-semiconductor structures has revolutionized information processing and storage. However, the limitations of silicon-based FETs in electrical switching have driven the search for new materials capable of overcoming these constraints. Electrostatic gating of competing electronic phases in a Mott material near its metal-to-insulator transition (MIT) offers the prospects of substantial modulation of the conducting electrons and electrical resistivity through small changes in band filling. While electrostatic control of the MIT has been previously reported, the advancement of Mott materials toward novel Mott-based transistors, MottFETs requires the realization of their unique physical properties in a solid-state device. In this study, we present gate control of electron correlation using a solid-state device utilizing the oxide Mott system La 1-x Sr x VO 3 as a correlated FET channel. We report on a gate resistance response that cannot be explained in a purely electrostatic framework. This behavior suggests an enhancement in effective mass and a reduction in effective carrier density as the system approaches its insulating state, consistent with theoretical predictions for Mott systems, suggesting at least 100× charge gain originating from the correlated behavior. These preliminary results pave the way toward the development of highly efficient, low-power electronic devices that could surpass the performance bottlenecks of conventional FETs by leveraging the electronic phase transitions of correlated electron systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Analysis of the inter-species power balance in JET plasmas

Most auxiliary heating methods provide heating to more than one particle species (electrons, ions, impurities) in a fusion plasma. This can lead to substantial temperature differences between species, depending on conditions such as heating power to the different species and collisionality, with temperature differences between species limited by inter-species thermal equipartition and transport. The analysis of the steady-state electron-ion and impurity-ion power balances presented in this paper are used for consistency-checking experimental ion and electron temperature measurements and for inferring the main ion temperature from measured impurity temperatures. As ion temperature measurements by charge exchange spectroscopy (CXS) based on impurity ions have become more difficult and time-consuming since the installation of the ITER-like wall (ILW) with Be and W PFC's, knowing the maximum sustainable temperature difference between ions and electrons, |T i -T e | allows rejecting erroneous measurements. It also obviates the need for an ion temperature measurement, if an electron temperature measurement is available and |T i - T e | cannot be larger than the combined errors of the underlying measurements. A power balance analysis is also required for estimating the errors of the ion and electron heat fluxes prior to any species-resolved transport analysis. The ion-impurity temperature differences are usually found to be small due to strong thermal equipartition between ion species. However, they can approach 10% in JET-ILW low density, high power discharges, such the ones under development for a future JET deuterium–tritium campaign (Joffrin et al 2019 Nucl. Fusion). This has a generally small, but not always negligible effect on the calculation of fusion reaction rates, which depend on main ion temperatures. An important outcome of this analysis is that temperature differences between impurity species are always much smaller than between the impurities and hydrogenic species and can usually be neglected. The article presents two methods for calculating the impurity-to-main ion temperature ratio. Finally, this analysis leads to a method for the reconstruction ion temperature profiles from ion temperature data available at only one or a small number of spatial locations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Optimized Highly Efficient SSCB Using Organic Substrate Packaging for Electric Vehicle Applications

Solid State Circuit Breakers (SSCBs) are an attractive protection solution for their arcless current interruption and fast actuation speeds over mechanical breakers. This paper proposes a Bidirectional SSCB (BSSCB) with a thermally defined and digitally controlled current time profile for fault protection in EV and other low-voltage DC systems. The paper proposes an organic packaging approach utilizing flex circuitry to develop a reliable, cost-effective power module for BSSCBs. The paper studies transient heat transfer in the power modules using finite element analysis (FEA). An RC themal ladder network is extracted to define a fusing curve. To demonstrate and verify the design, a 1kV/50 A SiC MOSFET BSSCB prototype is fabricated and tested, having a power density of 60 W/cm3 and 4x reduction in form factor over presently researched breakers. Also, given are results for 750 V/150 A operation showing interruption in 2.4 μs.

organic power packaging↗
DOE OSTI2025

Using Artificial Intelligence to Improve Reliability and Operational Efficiency of Small-Scale Hydroelectric Distributed Generation

Reliability and resilience are critical concerns for distributed generation (DG) at the rural electric level. The integration of renewable energy sources, such as small-scale hydroelectric distributed generators (hydro DGs), introduces operational challenges, particularly regarding aging infrastructure and grid stability. Artificial Intelligence (AI)-driven Machine Learning (ML) models and applications of Large Language Models (LLMs) offer promising solutions for optimizing DG operations and enhancing resilience. This paper explores AI-based models for improving efficiency, fault resolution, and outage mitigation in small-scale hydro DGs. Furthermore, it highlights the development of a centralized, AI-powered information portal for rural electric cooperatives and municipalities. The research evaluates hydro DG plant models and discusses the applicability of AI-powered question-answering tools for real-time operations, focusing on statistical data, load flow, voltage regulation, and generation power. The findings demonstrate AI’s potential to transform DG management to ensure greater stability and resilience in rural electric grids.

Bhattacharyya, Arjun [ORNL] (ORCID:000900060976046↗
DOE OSTI2023

A Stability Analysis Tool for Bulk Power Systems Using Black-Box Models of Inverter-Based Resources

This paper presents a small-signal stability analysis tool for large-scale power systems with high penetration of inverter-based resources (IBRs). Firstly, a network transfer function matrix (NTFM), which represents the information of the system topology, transmission lines, loads, IBRs locations, etc., is derived to model the entire power system network. Secondly, small-signal perturbation method is applied to obtain the sequence impedance/admittance models of the block-box IBRs considering the frequency cross-coupling effects. With the obtained NTFM as well as IBR models, a multi-input, multi-output (MIMO) feedback system is constructed, and the generalized Nyquist criterion (GNC)-based stability method is employed to analyze the stability of the entire power system. Furthermore, based on the developed stability analysis method, sensitivity analysis is conducted on an unstable case to identify which parameter has a high impact on the system stability. As a result, different test cases based on a modified IEEE 14- bus system as well as a reduced 240-bus WECC system are studied to verify the proposed stability analysis tool.

42 ENGINEERING↗
DOE OSTI2020

Noncontact Monitoring of Overhead Transmission Lines Using Space Potential Phasor Measurements

Power system reliability requirements necessitate the development of measurement systems to monitor the operational state of critical transmission lines. Here in this article, a novel noncontact method for monitoring overhead transmission lines is proposed. The method is based on measuring the amplitude and relative phase of the transmission line's space potential at two or more strategically located points in space along with the use of passive phase shifters to enhance the sensitivity of the measurements. Applications of voltage unbalance and conductor sag measurements are demonstrated along with the results of conductor sag measurements on an operating 230-kV transmission line. It is shown that using enhanced relative phase measurements can significantly improve the sensitivity of the measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform

Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged digital quantum resources, such as discrete-variable (DV) systems like qubits, rather than analog quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals—specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.

42 ENGINEERING↗
DOE OSTI2022

Cascade Models in Simulation of Extended Heavy Targets Irradiated by Accelerated Proton and Deuteron Beams

The paper presents a survey of the main numerical models used for simulation of interaction of accelerated particle beams with target nuclei. These models form the core of the software for simulation of various experiments and experimental facilities both for scientific and applied purposes. The beam and target parameters considered in detail in this study (protons and deuterons with energies from 0.66 to 4 AGeV and bulk U targets) cover the range of interest in development of new concepts of nuclear power production aided by accelerated particle beams.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗