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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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Four key operations-related costs are associated with the Space Station: (1) transportation, (2) data management, (3) sustaining enginenering, and (4) integrated logistics. Life cycle cost principles will be utilized by the Space Station Program to assess operating costs associated with any particular design 'improvement' opportunity.
Structural vibrations from a point force are modelled on a finite beam. This research explores the theoretical limit on controlling beam vibrations utilizing another point source as an active controller. Three different types of excitation are considered, harmonic, random, and transient. For harmonic excitation, control over the entire beam length is possible only when the excitation frequency is near a resonant frequency of the beam. Control over a subregion may be obtained even between resonant frequencies at the cost of increasing the vibration outside of the control region. For random excitation, integrating the expected value of the displacement squared over the required interval, is shown to yield the identical cost function as obtained by integrating the cost function for harmonic excitation over all excitation frequencies. As a result, it is always possible to reduce the cost function for random excitation whether controlling the entire beam or just a subregion, without ever increasing the vibration outside the region in which control is desired. The last type of excitation considered is a single, transient pulse. The form of the controller is specified as either one or two delayed pulses, thus constraining the controller to be casual. The best possible control is examined while varying the region of control and the controller location. It is found that control is always possible using either one or two control pulses.
GTI Energy (GTI) and team members Southern Company Services (SCS), Pacific Gas & Electric (PG&E) and the Electric Power Research Institute (EPRI) performed a Phase II Pre-Feed Study under contract DE-FE0032008 for Hydrogen Storage for Load-Following and Clean Power. The configuration of the proposed system consists of subsystems for on-site H 2 production, on-site H 2 storage (up to 54 MWth in commercial vessels) and H 2 combustion in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with an existing fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load and H 2 production is relatively constant by storing H 2 . The proposed system is an improvement over alternate low carbon dispatchable power options. Technoeconomic analyses show H 2 produced with GTI’s patented Compact Hydrogen Generator (CHG) with inherent carbon capture will be lower cost (Levelized Cost of Hydrogen, LCOH) relative to hydrogen produced with a Steam Methane Reformer (SMR) with an amine system for carbon capture. This lower cost hydrogen enables our integrated system to deliver electricity (Levelized Cost of Electricity, LCOE) at 17.4% lower cost relative to a SMR sourced H 2 -fired HRSG (with an amine system for carbon capture) – Steam Turbine Generator (STG). Our analysis using EPRI’s US REGEN macroeconomic model shows our system will have significant demand in the power market and therefore require significant capacity expansion (CHG plants built to deliver hydrogen) to deliver low cost, low carbon power. In Phase II, our Team has completed a detailed system definition including the development of process models, definition of battery limits, Process Flow Diagrams (PFDs), Piping and Instrumentation Drawings (P&IDs), and a plant layout. A preliminary design for the key components of the CHG was developed including component lists & specifications. An evaluation of environmental and permitting considerations was completed and included the development of an Environmental Information Volume (EIV). The duct burners, which are flexible and can burn hydrogen and/or natural gas, were defined and initial CFD analyses were completed.
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Energy storage is critical for overcoming challenges associated with the intermittency and the variable availability of renewable sources for decarbonizing the energy sector. Cryogenic energy storage (CES) is of interest due to its high technology readiness level, no geographical limitations, and moderate round-trip efficiency. The time-varying nature of demands and renewable availability needs to be considered at the design and integration stages of energy storage. We develop a mixed-integer nonlinear program (MINLP) model to obtain the energy storage costs on a daily basis for different scenarios that typically arise over an entire year. Using this optimization-based framework, we address key decision-making questions towards energy transition: What is the energy cost when CES is integrated with renewables and power plants? How does each scenario affect the overall energy cost? How much storage is needed for complete transition to renewables? What is the optimal integration towards 100% renewable energy? What are the optimal storage designs for both renewables and fossil-based power generation with current and future energy demands? Here, we discuss different scenarios and solutions to these questions.
Circuit-level metering technologies provide the ability to monitor individual circuits within an electrical panel in a building, providing detailed power and energy consumption data at a much more granular level than was previously achievable in a cost-effective manner. While the fundamental hardware components of circuit-level—split-core current transformers (CTs) and power monitoring meters—have existed for some time, the new offerings in the market have tightly integrated these components, lower costs, and have streamlined data organization, transport, and access via software solutions accessible through web and application programming interfaces (API). NREL evaluated Meazon’s single-circuit metering system. The evaluation of the equipment under test (EUT) focused on three aspects: (1) accuracy of the data provided by the system, (2) ease of installation of this technology and ease of data integration into existing U.S. General Services Administration (GSA) analytics platforms, and (3) total cost of ownership and cost-effectiveness of the technology. The metering technology was tested in a field deployment where it was installed in low and high-voltage commercial electrical panels in the César E. Chávez Memorial Building in Denver, Colorado. The goals were to assess the metering accuracy, the ease of installation and data retrieval, and the total cost of ownership and cost-effectiveness. This technology proved easy to install by a certified electrician who completed the install of 6 meters in 2 separate panels (120/208 V and 277/480 V) and 2 circuit disconnects (along with associated commissioning) at the César E. Chávez Memorial Building in less than one day. The technology was installed in high- and low-voltage panels and with limited space in the electrical room, demonstrating the applicability of this technology to almost all commercial buildings in the GSA portfolio. Primary considerations for this technology include appropriate sizing of CTs for each circuit, selection of loads/circuits/panels that are of high value for detailed submetering (e.g., tailored for high-load devices), and how GSA would like to integrate these data with its existing energy management infrastructure. Through the field evaluation, we demonstrated data integration from the vendor system into the primary software component on the GSA enterprise-level energy management and information system, GSA Link. Data from the circuit-level metering were integrated into this platform and used to perform FDD. This demonstrated the ability of the EUT to augment existing energy management and information systems in buildings where GSA Link is deployed and provides a pathway for delivering FDD at other buildings throughout the portfolio.
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The US electric grid relies on conventional fossil fuel power plants for reliable and secure power, but these plants suffer from physical and financial strain due to the influx of inexpensive and variable solar and wind electricity. Conventional power plants need to generate electricity flexibly and on-demand to accommodate these renewable resources on the grid. Integrating a low-cost thermal energy storage (TES) gives fossil assets the ability to regulate their output efficiently and optimize the plant operation to maximize revenue in the wholesale electricity market. Element 16’s TES concept uses sulfur, a byproduct of the oil & gas industry, as the storage media that is 10 times cheaper than molten salt used in commercial two-tank TES technology. In this project, the team completed a detailed feasibility and technoeconomic study establishing the impact, cost and performance of molten sulfur TES system integrated with fossil assets.
Lebesgue integration of derivatives of strongly-oscillatory functions is a recurring challenge in computational science and engineering. Integration by parts is an effective remedy for huge computational costs associated with Monte Carlo integration schemes. In case of Lebesgue integrals over a smooth manifold, however, integration by parts gives rise to a derivative of the density implied by charts describing the domain manifold. This paper focuses on the computation of that derivative, which we call the density gradient function, on general smooth manifolds. We analytically derive formulas for the density gradient and present examples of manifolds determined by popular differential equation-driven systems. Furthermore, we highlight the significance of the density gradient by demonstrating a numerical example of Monte Carlo integration involving oscillatory integrands.
Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.
A comprehensive techno-economic analysis of destabilized Li hydrides, used as thermal energy storage systems in concentrating solar power plants, is presented and discussed. Two systems, operating at temperatures on the order of 550–650 °C, are selected as thermal energy storage units for steam power plants, namely the Si-destabilized Li hydride (LiSi) and the Al-destabilized Li hydride (LiAl). Two thermal energy storage systems, operating at temperatures on the order of 700–750 °C, are selected for integration in supercritical CO2 power plants, namely the Si-destabilized Li hydride (LiSi) and the Sn-destabilized Li hydride (LiSn). Each storage system demonstrates excellent volumetric capacity, achieving values between 100 and 250 kWhth/m3. The LiSi-based thermal energy storage systems can be integrated with steam and supercritical CO2 plants at a specific cost between 107 US$/kWhth and 109 US$/kWhth, with potential to achieve costs on the order of 74 US$/kWhth under enhanced configurations and scenarios. The LiAl-based storage system has the highest potential for large scale applications. The specific cost of the LiAl system, integrated in solar steam power plants, is equal to approximately 74 US$/kWhth, with potential to reach values on the order of 51 US$/kWhth under enhanced performance configurations and scenarios.
Ceramic integration technologies enable hierarchical design and manufacturing of intricate ceramic and composite parts starting with geometrically simpler units that are subsequently joined to themselves and/or to metals to create components with progressively higher levels of complexity and functionality. However, for the development of robust and reliable integrated systems with optimum performance for high temperature applications, detailed understanding of various thermochemical and thermomechanical factors is critical. Different technical approaches are required for the integration of ceramic to ceramic and ceramic to metal systems. Active metal brazing, in particular, is a simple and cost-effective method to integrate ceramic to metallic components. Active braze alloys usually contain a reactive filler metal (e.g., Ti, Cr, V, Hf etc) that promotes wettability and spreading by inducing chemical reactions with the ceramics and composites. In this presentation, various examples of brazing of silicon nitride to themselves and to metallic systems are presented. Other examples of joining of ceramic composites (C/SiC and SiC/SiC) using ceramic interlayers and the resulting microstructures are also presented. Thermomechanical characterization of joints is presented for both types of systems. In addition, various challenges and opportunities in design, fabrication, and testing of integrated similar (ceramic-ceramic) and dissimilar (ceramic-metal) material systems will be discussed. Potential opportunities and need for the development of innovative design philosophies, approaches, and integrated system testing under simulated application conditions will also be presented.
The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.
Both direct current fast charging (DCFC) and Hydrogen stations are working to create successful long-term business models; however, analyses for DCFC and hydrogen fueling infrastructure are almost always performed separately. This work provides a detailed exploration of the benefit of integrating DCFC and hydrogen stations to lower the total system cost from load balancing and equipment cost sharing. To achieve this we have adapted the REopt optimization framework to simultaneously optimize the design and operation of integrated DCFC and H2 fueling station. Results indicate that 1) combining hydrogen fueling and DCFC stations can significantly reduce lifetime costs compared to separated stations. 2) Co-location with additional site load reduces DCFC costs, however, integration of DCFC with hydrogen provides an even greater cost reduction. 3) Adding PV to combined stations further reduces the lifetime station cost. 4) Capital investments in station combination today can help reduce the cost of operating DCFC tomorrow and 5) product diversification acts as a hedge against variability and enables a more dynamic response to market changes.
The energy use and costs of the on-site integrated energy system (OS/IES) which provides electric power from an on-site power plant and recovers heat that would normally be rejected to the environment is compared to a conventional system purchasing electricity from a utility and a phosphoric acid fuel cell powered system. The analysis showed that for a 500-unit apartment complex a fuel OS/IES would be about 10% more energy conservative in terms of total coal consumption than a diesel OS/IES system or a conventional system. The fuel cell OS/IES capital costs could be 30 to 55% greater than the diesel OS/IES capital costs for the same life cycle costs. The life cycle cost of a fuel cell OS/IES would be lower than that for a conventional system as long as the cost of electricity is greater than $0.05 to $0.065/kWh. An analysis of several parametric combinations of fuel cell power plant and state-of-art energy recovery systems and annual fuel requirement calculations for four locations were made. It was shown that OS/IES component choices are a major factor in fuel consumption, with the least efficient system using 25% more fuel than the most efficient. Central air conditioning and heat pumps result in minimum fuel consumption while individual air conditioning units increase it, and in general the fuel cell of highest electrical efficiency has the lowest fuel consumption.
Cost control must be implemented through the establishment of requirements and controlled continually by managing to these requirements. Cost control of the non-recurring side of life cycle cost has traditionally been implemented in both commercial and government programs. The government uses the budget process to implement this control. The commercial approach is to use a similar process of allocating the non-recurring cost to major elements of the program. This type of control generally manages through a work breakdown structure (WBS) by defining the major elements of the program. If the cost control is to be applied across the entire program life cycle cost (LCC), the approach must be addressed very differently. A functional breakdown structure (FBS) is defined and recommended. Use of a FBS provides the visibifity to allow the choice of an integrated solution reducing the cost of providing many different elements of like function. The different functional solutions that drive the hardware logistics, quantity of documentation, operational labor, reliability and maintainability balance, and total integration of the entire system from DDT&E through the life of the program must be fully defined, compared, and final decisions made among these competing solutions. The major drivers of recurring cost have been identified and are presented and discussed. The LCC requirements must be established and flowed down to provide control of LCC. This LCC control will require a structured rigid process similar to the one traditionally used to control weight/performance for space transportation systems throughout the entire program. It has been demonstrated over the last 30 years that without a firm requirement and methodically structured cost control, it is unlikely that affordable and sustainable space transportation system LCC will be achieved.
To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.
Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.