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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Internal Insulation and Corrosion Control of Molten Chloride Storage Tanks

The National Renewable Energy Laboratory (NREL) is leading a multi-national team to validate the potential of a chloride-based molten-salt system that uses a ternary blend of MgCl2/KCl/NaCl to provide higher temperature thermal energy storage capability, thereby allowing for higher efficiency in the power block of next-generation concentrating solar power systems. While higher thermal stability, greater operating temperature, and a more efficient power cycle are possible, the molten chlorides present several unique challenges, including the design of internal liners to prevent the corrosion and thermal stress of alloy tank shells. This work discusses issues and potential solutions related to containment of molten chloride salt, specifically the design of the molten salt storage tanks.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

HHL algorithm with mapping function and enhanced sampling for model predictive control in microgrids

Here, this paper presents a refined quantum Harrow Hassidim Lloyd (HHL) algorithm for microgrid control. The first novelty of the developed method is that a mapping shift function enables the original HHL algorithm to handle general linear equations with non-singular and indefinite matrix. Second, a method of Matrix Extension for Amplifying Sampling Probabilities of Intended Solution (ME-ASPI) is proposed to design the reformulated linear algebraic equations, allowing for improved sampling efficiency of the quantum tomography in the refined HHL algorithm. Then, we applied the method to solve the model predictive control (MPC) problem in nonlinear dynamical microgrids. Specifically, with the ME-ASPI method, the refined HHL algorithm can effectively obtain the intended partial optimal control inputs for MPC. The optimization of quadratic programming problem in each time step of MPC is transformed into a linear system problem, which is addressed by the proposed quantum solver through using only partial information, with the time complexity improved from $\mathscr{O}(\mathscr{N}^{2.37286})$ classically to $\mathscr{O}(\mathscr{N}^{2} log \mathscr{N}$ x $p$ log $p)$ in quantum. Numerical examples have validated the effectiveness of the refined HHL algorithm with the proposed mapping function and the ME-ASPI method. By leveraging quantum properties, the proposed method provides a hybrid quantum–classical framework for microgrid control. This generic method can also potentially tackle many other challenges in analyzing and controlling general complex engineered systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Electrical and Thermal Load Impacts of Three District Heating and Cooling Designs for an Existing Community in Washington, DC

District energy systems that provide building heating and cooling are a promising option to provide low-cost, energy efficient heating and cooling solutions for communities. As some buildings move to electrified heating designs, there may be significant increases in electric grid demand, particularly in the winter. District energy systems may be able to help reduce these high electrical demands on the electric grid, while also providing decreased overall energy consumption with an increased flexibility in electrical energy usage. To evaluate and compare district options for district-based heating and cooling, an existing neighborhood of Washington, DC consisting of 35 existing buildings was selected as a case study. This study models and compares a fourth generation (4G) district heating and cooling systems that provide hot and chilled water from a central plant directly to each prosumer and a fifth generation (5G) district heating and cooling systems that provide near-ambient water via geothermal boreholes to interface with an energy transfer station with a heat pump at each prosumer. These district systems are compared against a baseline of the non-connected buildings with their self-contained and current HVAC systems. The neighborhood was selected as a good candidate for a district system for its diversity of loads (mix of different commercial and property types) and the availability of building characteristics. URBANopt District Energy Systems (DES) was used to model the buildings and create initial Modelica models for the district systems. Finally, the DES models were tuned and simulated in Dymola, and the outputs were post-processed for verification and to calculate the electrical and thermal grid impact metrics. This is the first documentation of this workflow and its complete analysis. The three designed systems are compared via their grid metrics including: total energy consumption, electrical demand peak loads, daily peak-to-valley ratios, and system ramping. A detailed discussion is provided about how each system impacts and interacts with the electric grid.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Design and Validation of Mechanical & Autonomous Systems in Harsh Environments [Poster]

The autonomous systems within the Mobile Hot Cell provide advanced capabilities over traditional hot cells, pushing the boundaries of these systems in harsh environments. The degraded state of some radiological devices and the variety of designs present a series of challenges that require innovative tooling and procedural solutions. By leveraging technical knowledge and experience from disposition experts at SwRi and other institutions, initial design concepts were produced using rapid prototyping techniques. These concepts were then validated and optimized in a non-hazardous test bed, resulting in iterative improvements at minimal cost.

07 - ISOTOPES AND RADIATION SOURCES↗
DOE OSTI2025

Chemical trends favoring interstitial cluster formation in bcc high-entropy alloys from first-principles calculations

Achieving high strength and ductility is a common goal in structural alloy design. Body-centered cubic high-entropy alloys (HEAs) commonly highlight the conflict between these properties, with stronger alloys being brittle and vice versa. Recent reports suggest interstitial solutes can be used to overcome this trade-off, in some cases providing both strength and ductility enhancements. This effect has been correlated with interstitial cluster formation, although the conditions favoring their formation remain incompletely understood. Using first-principles calculations of solution energies and diffusivities, we provide insights into thermodynamic and kinetic factors favoring interstitial solute clusters. Among C, N and O solutes, O interstitials display most desirable diffusion kinetics. Further, the results highlight the importance of local composition fluctuations in the HEAs to enable the formation of clusters of appreciable size. The results are explained in terms of bonding and distortion trends across solutes and HEA compositions to provide guidelines for alloy design.

Borges, Pedro P P O↗
DOE OSTI2023

Generalized Theory and Realization of Continuously Loss-Programmable Bandpass Filtering Attenuators

With the increased demand for modern wireless systems in various applications, the need for adjustable radio frequency (RF) systems has dramatically increased. These modern systems rely on operating in the microwave frequency spectrum (1 GHz to 1 THz) without interference from other devices while also retaining the ability to detect very low and very high power signals simultaneously. There is also an ever-increasing demand for reducing the cost, size, weight, and power (C-SWaP) of these modern RF systems, driving the demand for more agile filters in the microwave frequency spectrum. In this paper, a generalized theory of bandpass filtering attenuators (filtenuators) is proposed. A filtenuator is a device that combines the frequency- selective characteristics of a filter and the loss-programmable characteristics of an attenuator into a single component. The loss- programmable aspect of the filtenuator is based on the tuning of a π-network of resistances, which are implemented using PIN diodes to control the individual resistance values electronically. A loss-programmable, third-order Chebyshev bandpass filtenuator is designed, fabricated, and measured to verify the generalized theory. The filtenuator is designed to operate at 1 GHz and have a tunable attenuation range of 2-10 dB. This proposed filtenuator demonstrates the feasibility of a tunable, low C-SWaP solution to increase RF system dynamic range and a design process that allows for future development of filtenuators.

42 ENGINEERING↗
DOE OSTI2026

Molecular Programming of Diorganyl Dichalcogenides for Rational Nanocrystal Design

Soft-chemistry nanocrystal synthesis leverages low-temperature, solution-phase reactions to access materials that can be kinetically stabilized rather than thermodynamically favored. Under such mild conditions, reaction pathways are governed not only by precursor composition but also by the molecular details that dictate how reactive atomic species are generated and delivered. Furthermore, harnessing this kinetic sensitivity offers a powerful opportunity: by deliberately programming precursor reactivity, nanocrystal composition, structure, and morphology can be rationally designed rather than empirically discovered.

Chalcogenides↗
DOE OSTI2022

Informing Nature-based Climate Solutions for the United States with the best-available science

Nature-based Climate Solutions (NbCS) are managed alterations to ecosystems designed to increase carbon sequestration or reduce greenhouse gas emissions. While they have growing public and private support, the realizable benefits and unintended consequences of NbCS are not well understood. At regional scales where policy decisions are often made, NbCS benefits are estimated from soil and tree survey data that can miss important carbon sources and sinks within an ecosystem, and do not reveal the biophysical impacts of NbCS for local water and energy cycles. The only direct observations of ecosystem-scale carbon fluxes, for example, by eddy covariance flux towers, have not yet been systematically assessed for what they can tell us about NbCS potentials, and state-of-the-art remote sensing products and land-surface models are not yet being widely used to inform NbCS policymaking or implementation. As a result, there is a critical mismatch between the point- and tree-scale data most often used to assess NbCS benefits and impacts, the ecosystem and landscape scales where NbCS projects are implemented, and the regional to continental scales most relevant to policymaking. Here, we propose a research agenda to confront these gaps using data and tools that have long been used to understand the mechanisms driving ecosystem carbon and energy cycling, but have not yet been widely applied to NbCS. Furthermore, we outline steps for creating robust NbCS assessments at both local to regional scales that are informed by ecosystem-scale observations, and which consider concurrent biophysical impacts, future climate feedbacks, and the need for equitable and inclusive NbCS implementation strategies. We contend that these research goals can largely be accomplished by shifting the scales at which pre-existing tools are applied and blended together, although we also highlight some opportunities for more radical shifts in approach.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Valuing Ecosystems in Equitable Energy Transition Planning

In this report we explore three areas of research and practice needed to scale clean energy sustainably: 1) advancing the predictive science to quantify positive and negative outcomes of energy development for the wellbeing of communities, environments, and disadvantaged groups; 2) scenario design using this science to shape renewable energy solutions for nation-wide decarbonization while delivering tangible, local benefits; and 3) participatory science-policy processes to understand what people want for the places where they live and work and how incorporating renewable energy can help or hinder their goals. Together these three components – quantifying social-ecological values, scenario design, and participatory processes – form the basis for a framework for valuing ecosystems to inform a more equitable energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Inverse design of pore wall chemistry and topology through active learning of surface group interactions

Design of next-generation membranes requires a nanoscopic understanding of the effect of biologically inspired heterogeneous surface chemistries and topologies (roughness) on local water and solute behavior. In particular, the rejection of small, neutral solutes, such as boric acid, poses a heretofore unsolved challenge. In prior work, a computational inverse design technique using an evolutionary optimization successfully uncovered new surface design strategies for optimized transport of water over solutes in smooth, model pores consisting of two surface chemistries. However, extending such an approach to more complex (and realistic) scenarios involving many surface chemistries as well as surface roughness is challenging due to the expanded design space. In this work, we develop a new approach that uses active learning to optimize in a reduced feature space of surface group interactions, finding parameters that lead to their assembly into ordered, optimal patterns. This approach rapidly identifies novel surface functionalizations that maximize the difference in water and boric acid transport through the nanopore. Moreover, we find that the roughness of the nanopore wall, independent of its chemistry, can be leveraged to enhance transport selectivity: oscillations in the pore wall diameter optimally inhibit boric acid transport by creating energetic wells from which the solute must escape to transport down the pore. Furthermore, this proof-of-concept demonstrates the potential for active learning strategies, in concert with molecular simulations, to rapidly navigate complex design spaces of aqueous interfaces and is promising as a tool for engineering water-mediated surface interactions for a broad range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

The ERL Facility PERLE at Orsay

The realisation of the LHeC and the FCC-eh at CERN require the development of the energy recovering technique in multipass mode and for large currents O(10) mA in the SRF cavities. For this purpose, a technology development facility, PERLE, is under design to be built at IJCLab Orsay, which has the key LHeC ERL parameters, in terms of configuration, source, current, frequency and technical solutions, cryomodule, stacked magnets. In this talk we review the design and comment on the status of PERLE.

Bogacz, Alex↗
DOE OSTI2023

Tabulated Database of Closed-Loop Geothermal Systems Performance for Cloud-Based Technical and Economic Modeling of Heat Production and Electricity Generation: Preprint

To better understand the heat production, electricity generation performance and economic viability of closed loop geothermal systems in hot-dry-rock, the Closed Loop Geothermal Group, a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and super-critical CO2) while varying seven continuous independent parameters of interest (i.e., mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an Organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the TEA (techno-economic analysis) script are provided.

co-axial↗
DOE OSTI2020

Design and performance of high-temperature furnace and cell holder for in situ spectroscopic, electrochemical, and radiolytic investigations of molten salts

To facilitate the development of molten salt reactor technologies, a fundamental understanding of the physical and chemical properties of molten salts under the combined conditions of high temperature and intense radiation fields is necessary. Optical spectroscopic (UV–Vis–near IR) and electrochemical techniques are powerful analytical tools to probe molecular structure, speciation, thermodynamics, and kinetics of solution dynamics. In this paper, we report the design and fabrication of three custom-made apparatus: (i) a multi-port spectroelectrochemical furnace equipped with optical spectroscopic and electrochemical instrumentation, (ii) a high-temperature cell holder for time-resolved optical detection of radiolytic transients in molten salts, and (iii) a miniaturized spectroscopy furnace for the investigation of steady-state electron beam effects on molten salt speciation and composition by optical spectroscopy. Initial results obtained with the spectroelectrochemical furnace (i) and high-temperature cell holder (ii) are reported.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

PPINN: Parareal physics-informed neural network for time-dependent PDEs

Physics-informed neural networks (PINNs) encode physical conservation laws and prior physical knowledge into the neural networks, ensuring the correct physics is represented accurately while alleviating the need for supervised learning to a great degree. While effective for relatively short-term time integration, when long time integration of the time-dependent PDEs is sought, the time–space domain may become arbitrarily large and hence training of the neural network may become prohibitively expensive. To this end, we develop a parareal physics-informed neural network (PPINN), hence decomposing a long-time problem into many independent short-time problems supervised by an inexpensive/fast coarse-grained (CG) solver. In particular, the serial CG solver is designed to provide approximate predictions of the solution at discrete times, while initiate many fine PINNs simultaneously to correct the solution iteratively. There is a two-fold benefit from training PINNs with small-data sets rather than working on a large-data set directly, i.e., training of individual PINNs with small-data is much faster, while training the fine PINNs can be readily parallelized. Consequently, compared to the original PINN approach, the proposed PPINN approach may achieve a significant speed-up for long-time integration of PDEs, assuming that the CG solver is fast and can provide reasonable predictions of the solution, hence aiding the PPINN solution to converge in just a few iterations. To investigate the PPINN performance on solving time-dependent PDEs, we first apply the PPINN to solve the Burgers equation, and subsequently we apply the PPINN to solve a two-dimensional nonlinear diffusion–reaction equation. Furthermore, our results demonstrate that PPINNs converge in a few iterations with significant speed-ups proportional to the number of time-subdomains employed.

42 ENGINEERING↗
DOE OSTI2024

Enhanced steam oxidation resistance of uranium nitride nuclear fuel pellets

Here, the steam oxidation resistance of UN and UN-(20 vol%)ZrN fuel pellets is evaluated to enhance understanding of steam corrosion mechanisms in advanced nuclear fuel materials. In situ neutron diffraction shows the modified UN fuel pellets form a (U 0.77 ,Zr 0.23 )N solid-solution and the sole crystalline oxidation product detected in bulk is (U 0.77 ,Zr 0.23 )O 2 . U 2 N 3 is not detected in significant quantities during the steam oxidation of UN or (U 0.77 ,Zr 0.23 )N and stable lattice parameters show that hydriding does not take place. Steam oxidation rates, obtained via sequential Rietveld refinement show how (U 0.77 ,Zr 0.23 )N has a higher activation energy (79 ± 1 kJmol -1 vs. 50 ± 5 kJmol -1 ), higher onset temperature (430 °C vs. 400 °C) and slower reaction rates for steam oxidation up to 616 °C, than pure UN. Throughout, both UN and (U 0.77 ,Zr 0.23 )N exhibit linear (non-protective) oxidation kinetics, signifying that degradation of the fuel pellets is caused by the evolution of gaseous products at the interface followed by oxide scale spallation. This quantitative and mechanistic understanding of material degradation enables better defined operating regimes and points towards (U,Zr)N solid solutions as a promising strategy for the design of advanced nuclear fuel materials with enhanced steam corrosion resistance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Investigating microstructural evolution in SolidStir™ extruded oxide dispersion strengthened 14YWT alloy fuel cladding tube

Structural components for extreme environments require advanced materials and manufacturing processes. One such advanced material is oxide dispersion strengthened (ODS) Fe–14 wt.%Cr–3W–0.4Ti–0.3Y 2 O 3 (14YWT), which is developed for components to be used in Gen IV and fusion nuclear reactors. However, the conventional manufacturing processes to produce components, such as fuel cladding tubes, either do not retain the desired microstructural attributes or are costly and less efficient. As a result, a more attractive option is a novel manufacturing process developed on the principle of friction stir welding or processing (FSW/P) and commercially referred to as SolidStir™ Extrusion (SSE). Here this study used the SSE technique to study the manufacturing and microstructural evolution of a fuel cladding tube made of ODS 14YWT alloy. The cladding extrusion by the SSE technique involved the use of ball-milled 14YWT powders with Y, Ti, and O in the solid solution and the use of a specially designed W-25Re-Hf tool for consolidation and extrusion of the powders. A scanning electron microscope (SEM), electron backscattered diffraction (EBSD), and transmission electron microscope (TEM) were utilized for microstructural characterization. A Keyence microscope captured macrostructural photographs of the extruded tube. EBSD examination of the extruded tube on both transverse and longitudinal cross-sections showed the presence of dynamically recrystallized grains and revealed that the average grain size of the transverse cross-section was smaller than that of the longitudinal cross-section. The texture was weak and consisted of some amount of shear texture. The presence of nano-oxide clusters or precipitates of Y, Ti, and O (pyrochlores) in the extruded tube was determined by TEM. Aging heat treatment caused the average precipitate size to decrease and the density to increase compared to the as-processed condition. The results indicated that SSE is a viable tool for manufacturing fuel cladding tubes with the desired microstructural attributes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗