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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Observation of quenching-induced magnetic flux trapping using a magnetic field and temperature mapping system

Highly efficient superconducting radio-frequency cavities exhibit low heat loss and are used as components in accelerators and superconducting devices due to their high Q-values. The precise location of magnetic flux trapping in cavities is necessary to identify its effects on the performance of superconducting cavities. In this study, we report a new combined mapping system to measure the temperature and magnetic field on the equator. The proposed system comprehensively maps local magnetic field changes as magnetic flux trapping due to quenching. Our experimental results show that magnetic flux trapping due to quenching increases the local surface resistance of superconducting cavities at 2 K. Thus, the proposed system elucidates the relationship between local flux trapping due to quenching and surface resistance in superconducting cavities and highlights the effect of quenching on the surface resistance. This system can aid in the development of superconducting cavities with higher Q values.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

PyPVRPM: Photovoltaic Reliability and Performance Model in Python

The ability to perform accurate techno-economic analysis of solar photovoltaic (PV) systems is essential for bankability and investment purposes. Most energy yield models assume an almost flawless operation (i.e., no failures); however, realistically, components fail and get repaired stochastically. This package, PyPVRPM, is a Python translation and improvement of the Language Kit (LK) based PhotoVoltaic Reliability Performance Model (PVRPM), which was first developed at Sandia National Laboratories in Goldsim software (Granata et al., 2011) (Miller et al., 2012). PyPVRPM allows the user to define a PV system at a specific location and incorporate failure, repair, and detection rates and distributions to calculate energy yield and other financial metrics such as the levelized cost of energy and net present value (Klise, Lavrova, et al., 2017). Our package is a simulation tool that uses NREL’s Python interface for System Advisor Model (SAM) (National Renewable Energy Laboratory, 2020b) (National Renewable Energy Laboratory, 2020a) to evaluate the performance of a PV plant throughout its lifetime by considering component reliability metrics. Besides the numerous benefits from migrating to Python (e.g., speed, libraries, batch analyses), it also expands on the failure and repair processes from the LK version by including the ability to vary monitoring strategies. These failures, repairs, and monitoring processes are based on user-defined distributions and values, enabling a more accurate and realistic representation of cost and availability throughout a PV system’s lifetime.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Preliminary report on applications of machine learning techniques to the Nevada play fairway analysis

We are applying machine learning (ML) techniques, including training set augmentation and artificial neural networks, to mitigate key challenges in the Nevada play fairway project. The study area includes ~85 active geothermal systems as potential training sites and >12 geologic, geophysical, and geochemical features. The main goal is to develop an algorithmic approach to identify new geothermal systems in the Great Basin region. Major objectives include: 1) integrate ML techniques into the geothermal community; 2) develop open community datasets, whereby all play fairway and ML datasets and algorithms are publicly released and available for modification by various user groups; 3) identify data acquisition targets with high value for future work; 4) identify new signatures to detect blind geothermal systems; and 5) foster new capabilities for characterizing subsurface temperature and permeability. Initially, ML techniques are being applied to the same play fairway datasets and workflow. ML will then be applied to both enhanced and additional datasets, with modification of the PFA workflow to incorporate the new datasets. Finally, ML will be applied to define new workflows using the enhanced and additional datasets. An algorithmic approach that empirically learns to estimate weights of influence for diverse parameters can potentially scale and perform better than the play fairway analysis. Initial work on this project has involved 1) evaluating potential positive and negative training sites, 2) transformation of datasets into formats suitable for ML, and 3) initial development and testing of ML techniques.

58 GEOSCIENCES↗
DOE OSTI2022

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE [Slides]

Depending on the system, energy, and/or nuclide, altering the number of latent generations can significantly impact generated sensitivity coefficients. In general, as the number of latent generations increases, the accuracy of the generated sensitivity value compared with the DP value increases and there is a significant increase in the uncertainty with generated sensitivity values. IFP generated sensitivities appear to be more stable than those with CLUTCH. Complex systems, even with IFP and increased latent generations can still produce poor results (i.e., MPC- 32). This reiterates the importance of performing DPs to confirm sensitivities. IFP-Shift and CLUTCH can take advantage of parallel computing abilities. Work continues in this area as additional parameters and calculational methods are examined to provide analysts insights to successfully generating sensitivity coefficients for confirmatory analyses and validation efforts.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Experimental Investigation of Barium Sources and Fluid–Rock Interaction in Unconventional Marcellus Shale Wells Using Ba Isotopes

Produced waters from unconventional Marcellus Shale gas wells have anomalously high barium (Ba) concentrations and yield some of the isotopically heaviest Ba measured to date. Experiments were conducted to constrain the source of Ba in these fluids and the controls on barite (BaSO 4 ) precipitation and dissolution in oil and gas wells. Experiments simulating the acidizing stage evaluated the solubility of pure barite and drilling mud in 2 M HCl at 80 °C for periods of 2, 6, and 48 h and resulted in <0.01% barite dissolution with no appreciable change in δ 138 Ba ( 138 Ba/ 134 Ba normalized to NIST standard 3104a). Static autoclave experiments conducted at 66 °C and 20.7 MPa with combinations of ground Marcellus Shale solids and/or barite-bearing drilling mud with synthetic low-Ba fracturing fluid resulted in decreased Ba concentrations in the fluid, with the largest decrease in the shale-only run. Fluid δ 138 Ba values increased by about 0.5‰ as Ba concentrations decreased, consistent with closed-system Rayleigh fractionation. Flow-through experiments in Marcellus Shale core conducted for 28 days resulted in effluent Ba concentrations an order of magnitude lower than the influent, while sulfate concentrations increased over time. Effluent δ 138 Ba values increased over the first 12 days and plateaued at about 1‰ higher than the influent. Modeling suggests a combination of the release of labile shale Ba and barite precipitation. This work indicates that the processes of Ba release from fluid–shale interactions and barite precipitation in fractures and the well bore, while capable of producing high δ 138 Ba fluids, are unlikely to generate fluids with high-Ba concentrations and δ 138 Ba values like those in Marcellus-produced waters. As a result, we find that the release of sulfate from shale pyrite oxidation rapidly catalyzes barite precipitation and that dissolution of drilling mud barite or natural barite in the shale is unlikely to be the major source of Ba in Marcellus-produced waters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Concentrating photovoltaic retrofit for existing parabolic trough solar collectors: Design, experiments, and levelized cost of electricity

Photovoltaics and concentrating solar thermal power are two ways for generating electricity from sunlight, albeit through different methods. Parabolic trough style powerplants represent 3.6 GW of electricity production, but many of these plants are aging and being replaced with photovoltaics. An alternative option that could be employed to leverage the sunk capital cost associated with the primary optics would be the design of a pure photovoltaic retrofit working within the existing plant architecture. Here, a secondary optical concentrator is designed to use the existing primary optics of a parabolic trough type solar thermal powerplant. The design is a v-shaped secondary concentrator resulting in a predicted concentration ratio on a 20 mm wide target of 94. The concentrating photovoltaic receiver for retrofit of an RP-3 based parabolic trough has been constructed using multi-junction concentrator photovoltaic cells and experimentally demonstrated here for the first time. Calculated performance of the cells based on cell specifications should result in 31% efficiency at 85 °C. On-sun efficiencies were measured at an average value of 21% with operational temperatures between 55 and 120 °C. Levelized cost of electricity calculations predict the system to have the potential to be below 7¢/kWh based on predicted efficiencies and 13¢/kWh based on the measured values at cell costs of $5/cm 2 .

14 SOLAR ENERGY↗
DOE OSTI2022

Realistic simulations of spin squeezing and cooperative coupling effects in large ensembles of interacting two-level systems

We describe an efficient numerical method for simulating the dynamics of interacting spin ensembles in the presence of dephasing and decay. The method builds on the discrete truncated Wigner approximation for isolated systems, which combines the mean-field dynamics of a spin ensemble with a Monte Carlo sampling of discrete initial spin values to account for quantum correlations. Here we show how this approach can be generalized for dissipative spin systems by replacing the deterministic mean-field evolution by a stochastic process, which describes the decay of coherences and populations while preserving the length of each spin. We demonstrate the application of this technique for simulating nonclassical spin-squeezing effects or the dynamics and steady states of cavity QED models with 10 5 interacting two-level systems. This opens up the possibility to perform accurate real-scale simulations of a diverse range of experiments in quantum optics or with solid-state spin ensembles under realistic laboratory conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Online Control of Process Variance Using Feedback

For many stochastic control problem formulations, design objectives typically include constraining the covariance of the outputs of the system. Recent engineering challenges have demonstrated an interest in controlling system output covariances to a setpoint. However, open-loop control of system output covariance can be exceptionally challenging when the system has significant plant uncertainties. This paper explores closed-loop control of the system’s output covariance using a windowed variance function. The stochastic nature of the windowed variance feedback means that root locus and other classical control design techniques cannot be immediately used. Expected value analysis is used to generate transfer functions for the average response of such systems, and the results are used to design controllers. Stochastic simulations are presented to verify the analytical results and make other observations concerning closed-loop variance control.

Bieniek, Mitchell↗
DOE OSTI2024

Topology property analysis and application of stable time-delay regions for linear multiple time-delay systems

This study examines the relationship between the topology of stable time-delay regions and the stability analysis of an linear multiple time delay system. To analyze the topology of stable time-delay regions, we construct a function with a value equal to zero for the time-delay points on the boundaries of stable time-delay regions. The function is continuous and differentiable in the whole defining field with a global minimum of zero so that we can locate the boundaries by minimizing the value of the function. Based on the topology analysis, we proposed a performance validation approach for controllers that are designed to stabilize the system using feedback signals with time delays. The method based on the topology analysis is simple and reliable so that can deal with a linear time-invariant system with high order and multiple time delays (more than 3). The example case study shows that the above method is reliable and enables ultra-low latency coordination and control for the future power grid with ubiquitous power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Real-time series resistance monitoring in photovoltaic systems

A device includes at least one processor configured to determine a target irradiance value based on an operating current value of a photovoltaic (PV) device, a short-circuit current value of the PV device, and an operating irradiance value of the PV device. The at least one processor is also configured to determine an open-circuit voltage value of the PV device at the target irradiance value, determine a series resistance value of the PV device based on an operating voltage value of the PV device, the operating current value, and the open-circuit voltage value at the target irradiance value, and execute at least one programmatic action based on the series resistance value.

14 SOLAR ENERGY↗
DOE OSTI2024

Direct Power Control of Back to Back Modular Multilevel Converter with Advanced Grid Support Functions for Grid Forming Application

Possibility of using back-to-back modular multilevel converter system with a direct power control architecture has been investigated in this paper. The rectifier side is controlled to be in grid following mode whereas the inverter side is controlled in grid forming mode. Both the sides’ local controllers use Lyapunov energy function based architecture to accomplish the objective of active and reactive power control as well as maintaining a fixed user defined voltage over the dc bus on the rectifier side. Therefore, the proposed direct power control architecture has embedded dc bus control architecture to maintain fixed user defined value of the capacitors. Similar architecture is implemented on the inverter side to accomplish either voltage control during grid forming or power control during grid following. Advanced grid support functionalities based on IEEE-1547-2018 is implemented and utilized to generate the reference values for either the rectifier or the inverter sides. The overall system is modeled based on MATLAB/Simulink and PLECS domain and various important case studies to verify the efficacy of the overall system has been presented.

direct power control (DPC)↗
DOE OSTI2023

Techno-Economic Analysis and Optimization of a Compressed-Air Energy Storage System Integrated with a Natural Gas Combined-Cycle Plant

To address the rising electricity demand and greenhouse gas concentration in the environment, considerable effort is being carried out across the globe on installing and operating renewable energy sources. However, the renewable energy production is affected by diurnal and seasonal variability. To ensure that the electric grid remains reliable and resilient even for the high penetration of renewables into the grid, various types of energy storage systems are being investigated. In this paper, a compressed-air energy storage (CAES) system integrated with a natural gas combined-cycle (NGCC) power plant is investigated where air is extracted from the gas turbine compressor or injected back into the gas turbine combustor when it is optimal to do so. First-principles dynamic models of the NGCC plant and CAES are developed along with the development of an economic model. The dynamic optimization of the integrated system is undertaken in the Python/Pyomo platform for maximizing the net present value (NPV). NPV optimization is undertaken for 14 regions/cases considering year-long locational marginal price (LMP) data with a 1 h interval. Design variables such as the storage capacity and storage pressure, as well as the operating variables such as the power plant load, air injection rate, and air extraction rate, are optimized. Results show that the integrated CAES system has a higher NPV than the NGCC-only system for all 14 regions, thus indicating the potential deployment of the integrated system under the assumption of the availability of caverns in close proximity to the NGCC plant. The levelized cost of storage is found to be in the range of 136–145 $/MWh. Roundtrip efficiency is found to be between 74.6–82.5%. A sensitivity study with respect to LMP shows that the LMP profile has a significant impact on the extent of air injection/extraction while capital expenditure reduction has a negligible effect.

25 ENERGY STORAGE↗
DOE OSTI2021

Moving toward a framework for electricity and heat equivalence in energy systems analysis

Sustaining, maintaining, and upgrading the electricity grid, while meeting decarbonization goals is a challenge facing policymakers, regulators, grid operators, and investors. Simultaneously meeting demands for future capacity, retiring older inefficient technologies, and addressing externalities from energy production and use requires more diverse and inclusive technologies to avoid constraints and shortfalls in grid capability. Changing the energy production paradigm by encouraging alternative technologies was a key driver for FERC Order 2222. This stimulus for developing new small-scale generation will complement and supplement the existing fleet only if it attracts new investment. This investment must reflect technology that goes beyond the energy-only characteristics of traditional generation, creating systems where suites of energy-equivalent outputs are enhanced by environmental quality benefits and offsets. We use energy system designs to highlight the contribution that measuring and accounting for equivalency values provides net increases in capacity, electricity, and alternative fuels while simultaneously reducing carbon waste impacts.

42 ENGINEERING↗
DOE OSTI2020

Evaluation of Detritiation Strategies for Mitigating Tritium Releases

Tritium confinement is performed using different barriers to minimize releases to the environment. Primary confinement is usually performed by process piping and components, secondary confinement typically by inerted gloveboxes connected to a continuously operating tritium stripper system. Some facility designs employ tertiary tritium confinement by using process room confinement with a tritium stripper system activated after an accident to further mitigate tritium releases to the environment. Secondary confinement of some tritium systems such as radiation-hardened or shielded-cell enclosures are not easily achieved using designs for inerted glovebox. These enclosures can be challenging to seal for secondary tritium confinement due to heating, ventilation, and air conditioning (HVAC) needs for temperature control, as well as feedthroughs for equipment and instrumentation, are potential pathways for tritium leaks or loses. Additional tritium leak paths can be created in secondary confinement enclosures due to a Design Basis Accident (DBA) seismic event. These new, larger tritium leak rates from the DBA event are usually not part of the stripper system design basis so all tritium released to the secondary confinement enclosure is assumed released to the environment. Detritiation strategies for shielded enclosures and/or gloveboxes with significant leak rates are necessary to minimize off-site radiological dose consequences. To address this, the relationship between the confinement system leak rate and stripper system (recirculating) flow rate was evaluated to meet prescribed maximum allowable environmental tritium emissions from the event. The simple analysis described assumes a constant leak rate from the confinement system (i.e. shielded enclosure or glovebox) while a recirculating stripper system strips tritium from the system– a competition between tritium release and tritium recovery. At a high level, the resulting expression summarizes the relationship between system leak rate (F L ) and stripper flow rate (F S ) relative to allowable tritium release (Q A ) and initial tritium release (Q 0 ): $\frac{F_L}{F_s}$ ≈ $\frac{Q_A}{Q_0}$. This report derives the relationship between these parameters, examines the impact of finite stripping times followed by purging of the stripped volume. The analysis provides example results for up to 30 gram tritium releases: the maximum tritium inventory of a Hazard Category III (Department of Energy) Nuclear Facility. The detritiation model presented represents a high-level analysis of tritium recovery versus losses for “leaky” confinement enclosures such as shielded cells after large tritium releases. Key parameters for doing the analyses are the system leak rate, stripper flow rate, initial tritium release, and allowable tritium release values. The analyses show a proportional decrease in releases with reduction in initial tritium release but a non-linear increase in tritium recovery with increased stripper flow rate or reduced leak-rate. The analyses also apply to glovebox confinement systems which could have significant increases in leak rates after a DBA. The analysis recognizes but does not include tritium absorption followed by re-emission from the walls of the confinement volume – an analysis which could be pursued in future studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Design of a High-Pressure Fuel System for Use with Dimethyl Ether

The paper documents the modeling and experimental work on a common rail fuel injection system for Dimethyl Ether, a potential diesel substitute with a low carbon intensity signature. The DME fuel system is deployed on a light duty 2.2L compression ignition engine. The paper describes the injector optimization to shift to higher flows to account for the lower heating value and density of the DME when compared to diesel. The type of the injection system used for the DME application is an advanced rendering of the Common rail noted for a one-piece piston-needle injector construction and a solenoid driven spill valve featuring a pressure balanced poppet. A dedicated high-pressure fuel pump designed to pressurize DME is used. The design results in a fast acting open and close injection event, reduced leakage, with reduced cavitation in the fuel injector volume. Design parameters for system optimization included fill and spill orifices, needle lift, bias spring, and injector hole size. The design model provides good correlation of the instantaneous rates of injection with experiments across a wide range of pressure and injection timings. Proposed performance milestones for the design included similar DME injection duration to the diesel counterpart for same fuel energy injected into the cylinder to retain high engine cycle efficiency. Here, the dedicated DME design provided reduced hydraulic delays of 50%. Tests demonstrated sustained operation at pressures of 1000 bar, with capability to reach 1500bar. Durability tests showed no cavitation-deterioration over a 200-hour test cycle by means of spray imaging and hardware inspection.

De Ojeda, William [WM International Engineering, L↗
DOE OSTI2022

Potential Roles For Demand Response in More-Electrified Futures

Power systems, both supply- and demand-side, are rapidly evolving due to technological change and various policy goals. This talk will describe potential roles for demand response in future power systems serving more electrified loads (including transport) and with higher shares of variable renewable generation. Starting from a broad definition of demand response as any change imposed on demand-side end-use operations meant to support power grid functionalities, we draw on a number of past and ongoing research topics to provide insight into the value of different kinds of demand response in different kinds of power systems.

demand response↗
DOE OSTI2025

High Power Density, Carbon Neutral Electrical Power Generation for Air Vehicles

The synergistic integration of a Solid Oxide Fuel Cell-Combustor (SOFC-C) with a turbogenerator (TG) will provide a very high fuel-to-electricity conversion efficiency while maintaining high power-to-weight ratio during high-altitude flight. The proposed SOFC-C-TG power generation technology exceeds the REEACH technical performance targets (TPT). This unique concept addresses many of the challenges faced in all electric propulsion-based aviation. The system has high part-load efficiency (more than 65% lower heating value (LHV)) during long cruise times, load following capability, high-power capacity at high altitudes adapting to low temperatures and pressures, rapid startup time of less than 30 minutes (proven with current SOFC technology), high power density (more than 3.2 kW/kg), efficient thermal management, and a foundation for a compact, efficient electrical storage and power generation system (ESPG). The SOFC-C concept achieves the technology targets by reducing the complexity of traditional fuel cell-gas turbine hybrid systems (FC-GT). The SOFC-C does not require heat exchangers and dramatically reduces the balance of plant increasing power density and performance in efficiency. The reduction in mass through elimination of heat exchangers, external reformer, and other components dramatically decreases the overall thermal dampening of the system which enables rapid startup and load following capability. Direct control of the cathode inlet temperature of the SOFC-C enables rapid warm-up of the SOFC tubes with the ability to reach operating temperature and full power in less than 30 minutes.

03 NATURAL GAS↗
DOE OSTI2024

Maximizing energy efficiency in wastewater treatment plants: A data-driven approach for waste heat recovery and an economic analysis using Organic Rankine Cycle and thermal energy storage

Maximizing energy efficiency through waste heat recovery (WHR) processes is crucial for sustainable and ecofriendly operations across multiple industries, notably in wastewater treatment plants (WWTPs). This work proposes a comprehensive approach for assessing the WHR feasibility in WWTPs, structured in two main objectives. Firstly, an Artificial Neural Network (ANN) model is developed to accurately predict WHR based on operational data, including biogas temperature, biogas pressure, daily production in kWh, and WHR values in kWh th . The second objective focuses on economically evaluating the WHR feasibility based on the estimated WHR values obtained by the ANN model, and then realistically assessing the economic feasibility of integrating the Organic Rankine Cycle (ORC) and Seasonal Thermal Energy Storage (STES) systems. With an application to the As-Samra WWTP located in Jordan, the developed ANN model demonstrates promising results in the validation phase, with a root mean square error (RMSE) of 2206 kWh/day, a mean absolute error (MAE) of 1674 kWh/day, and an R-squared (R 2 ) value of 68%. On the other hand, the economic analysis reveals that an optimal ORC system of 412.14 kW e capacity yields a Net Present Value (NPV) of 2.09 million US dollars, a Levelized Cost of Energy (LCOE) of 0.0749 USD/kWh, a Payback Period (PBP) of 4.8 years, and annual revenues of 428 kUSD. This work also investigates the techno-economic feasibility of integrating ORC-STES. Results indicate that the LCOE and PBP are highly affected by the ORC's capital cost, and integrating STES increases the LCOE to 0.0824 USD/kWh, rendering its integration with ORC infeasible. In conclusion, this study aims to advance the understanding and application of WHR in WWTPs, paving the way for more efficient and sustainable practices in the field.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗