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DOE OSTI2024

Modeling direct air carbon capture and storage in a 1.5 °C climate future using historical analogs

Limiting the rise in global temperature to 1.5 °C will rely, in part, on technologies to remove CO 2 from the atmosphere. However, many carbon dioxide removal (CDR) technologies are in the early stages of development, and there is limited data to inform predictions of their future adoption. Here, we present an approach to model adoption of early-stage technologies such as CDR and apply it to direct air carbon capture and storage (DACCS). Our approach combines empirical data on historical technology analogs and early adoption indicators to model a range of feasible growth pathways. We use these pathways as inputs to an integrated assessment model (the Global Change Analysis Model, GCAM) and evaluate their effects under an emissions policy to limit end-of-century temperature change to 1.5 °C. Adoption varies widely across analogs, which share different strategic similarities with DACCS. If DACCS growth mirrors high-growth analogs (e.g., solar photovoltaics), it can reach up to 4.9 GtCO 2 removal by midcentury, compared to as low as 0.2 GtCO 2 for low-growth analogs (e.g., natural gas pipelines). For these slower growing analogs, unabated fossil fuel generation in 2050 is reduced by 44% compared to high-growth analogs, with implications for energy investments and stranded assets. Residual emissions at the end of the century are also substantially lower (by up to 43% and 34% in transportation and industry) under lower DACCS scenarios. The large variation in growth rates observed for different analogs can also point to policy takeaways for enabling DACCS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2003

An Integrated Magnetic Circuit Model and Finite Element Model Approach to Magnetic Bearing Design

A code for designing magnetic bearings is described. The code generates curves from magnetic circuit equations relating important bearing performance parameters. Bearing parameters selected from the curves by a designer to meet the requirements of a particular application are input directly by the code into a three-dimensional finite element analysis preprocessor. This means that a three-dimensional computer model of the bearing being developed is immediately available for viewing. The finite element model solution can be used to show areas of magnetic saturation and make more accurate predictions of the bearing load capacity, current stiffness, position stiffness, and inductance than the magnetic circuit equations did at the start of the design process. In summary, the code combines one-dimensional and three-dimensional modeling methods for designing magnetic bearings.

Provenza, Andrew J.↗

DOE OSTI2024

Development of an immersion fiber optic Raman probe for real-time analysis of molten materials

This study presents an advancement in high-temperature Raman spectroscopy, specifically for analyzing molten materials. It introduces an approach by integrating a fiber-optic Raman probe with a copper block protection system designed to endure extreme thermal conditions. The copper block features an open port designed to accommodate an external telescope with a 3 cm focal length, enabling Raman spectra collection in challenging high-temperature environments. A built-in gas channel ensures a continuous flow of argon gas to prevent flux intrusion. The robust copper block acts as a reliable shield, safeguarding the fiber-optic Raman probe within molten materials. This enhancement maintains the probe's integrity and significantly improves its resilience, making it ideal for rigorous investigations of molten substances. This advancement is particularly relevant in metallurgy, where flux materials impact production quality and efficiency. The ability to acquire Raman signals under elevated thermal conditions offers opportunities for studying molecular dynamics, compositional changes, and chemical interactions within molten substances. This introduced direct immersion probing technique has implications, benefiting both scientific and industrial fields. It holds promise for advancing research and exploration in various contexts, from fundamental scientific inquiries to practical applications in metallurgical processes, where flux materials are critical for optimizing production quality and efficiency. Furthermore, this approach enhances the capabilities of high-temperature Raman spectroscopy, making it a valuable tool for investigating molten materials and their properties in diverse settings.

Argon↗

DOE OSTI2023

Direct prediction of inelastic neutron scattering spectra from the crystal structure*

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Development of Analysis Methods that Integrate Numeric and Textual Equipment Reliability Data

Within the Light Water Reactor Sustainability (LWRS) program, the Risk-Informed Systems Analysis (RISA) Pathway is performing collaborative research on the development and deployment of technologies designed to assist operating nuclear power plants (NPPs) to reduce operating costs improve plant reliability and availability. One of the RISA research areas is focusing on the development of methods and tools designed to optimize plant operations (e.g., maintenance/replacement schedules, optimal maintenance postures for plant structures, systems, and components [SSCs]) in a manner that is more cost effective than current approaches and makes better use of available SSC health data. The Risk-Informed Asset Management (RIAM) project targets this research area by creating a direct bridge between component equipment reliability (ER) data and system engineer decision making regarding maintenance activity scheduling and component aging management. In this respect, one challenge that NPP system engineers are facing is that the amount of ER data being continuously generated is not only extremely large in size, but it comes in different forms: textual (e.g., condition or maintenance reports) and numeric (e.g., generated by monitoring systems). All these data elements provide them with valuable insights and information regarding: 1) the discovery of anomalous behaviors or degradation trends, 2) the identification of the possible causes behind such behaviors/trends, and 3) the prediction of their direct consequences. However, several challenges have proved to be roadblocks to this process. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers/databases), others are conceptual in nature: data elements come in different formats (e.g., numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). The activities performed by the RIAM project during FY23 directly tackles the need to simultaneously integrate the analysis of ER data in all its forms, numeric and textual. Note that such task has never been performed before due to the complexity of the systems under consideration but, most importantly, because of the technical challenges behind the harmonization of ER data formats and the lack of adequate computational methods to analyze them. Our approach borrows ideas and concepts from the medical field where integration of several data sources is vital to assist medical practitioners to perform correct diagnosis and indicate optimal treatments. In our view a NPP asset is equivalent to a patient in a medical context. The main difference is the complexity of a human body is a magnitude more complex when compared to typical assets commonly present in NPPs (e.g., centrifugal pumps, or motor operated valves). This simplifies our first requirement when analyzing heterogenous ER data formats: to put data into “context”. Context is here intended as the additional piece of information that is needed by ER data analysis tools to understand what these data elements are referring to, i.e., which king of knowledge they are generating. In our context, this knowledge can be translated into models that capture the form and functional architecture of assets/systems, their dependencies, and how they interact. These models actually emulate the knowledge that that NPP system engineers possess about assets and systems; this is their key of success when analyzing ER data, their challenge is ability to handle large amount of data. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional, i.e. cause-effect, relations. Then, ER data elements are processed by identifying first of all which elements of the developed MBSE elements they are referring to. For numeric ER data this task is fairly easy since it is possible to precisely pinpoint what MBSE elements the corresponding sensor are observing (e.g., bearing temperature of a centrifugal pump). Task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process as “knowledge extraction”. Once again, we borrow the experience in the medical field where methods to extract knowledge from textual data have been developed in the past decade. The missing element for us is the availability of a complete dictionary of NPP related concepts (in addition to the MBSE models presented earlier) that can put “text into context”. In FY23, such dictionary has been developed along with all the computational elements required for knowledge extraction. Lastly, once numeric and textual ER data elements have been processed and “understood”, then the last step is the discovery of possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if the

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Simulation-aided occupant-centric building design: A critical review of tools, methods, and applications

Occupants are active participants in their built environment, affecting its performance while simultaneously being affected by its design and indoor environmental conditions. With recent advances in computer modeling, simulation tools, and analysis techniques, topics such as human-building interactions and occupant behavior have gained significant interest in the literature given their premise of improving building design processes and operating strategies. In practice, the focus of occupant-centric literature has been mostly geared towards the latter (i.e., operation), leaving the implications on building design practices underexplored. This paper fills the gap by providing a critical review of existing studies applying computer-based modeling and simulation to guide occupant-centric building design. The reviewed papers are organized along four main themes, namely occupant-centric: (i) metrics of building performance, (ii) modeling and simulation approaches, (iii) design methods and applications, and (iv) supporting practices and mechanisms. Important barriers are identified for a more effective application of occupant-centric building design practices, including the limited consideration of metrics beyond energy efficiency (e.g., occupant well-being and space planning), the limited implementation and validation of the proposed methods, and the lack of integration of occupant behavior modeling in existing building performance simulation tools. Finally, future research directions are discussed, covering large-scale international data collection efforts to move from generic assumptions about occupant behavior to specific/localized knowledge, improved metrics of measuring building performance, and improved industry practices, such as building codes, to promote an occupant-in-the-loop approach to the building design process.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1995

Scramjet Performance Assessment Using Water Absorption Diagnostics (U)

Simultaneous multiple path measurements of temperature and H2O concentration will be presented for the AIMHYE test entries in the NASA Ames 16-Inch Shock Tunnel. Monitoring the progress of high temperature chemical reactions that define scramjet combustor efficiencies is a task uniquely suited to nonintrusive optical diagnostics. One application strategy to overcome the many challenges and limitations of nonintrusive measurements is to use laser absorption spectroscopy coupled with optical fibers. Absorption spectroscopic techniques with rapidly tunable lasers are capable of making simultaneous measurements of mole fraction, temperature, pressure, and velocity. The scramjet water absorption diagnostic was used to measure combustor efficiency and was compared to thrust measurements using a nozzle force balance and integrated nozzle pressures to develop a direct technique for evaluating integrated scramjet performance. Tests were initially performed with a diode laser tuning over a water absorption feature at 1391.7 nm. A second diode laser later became available at a wavelength near 1343.3 nm covering an additional water absorption feature and was incorporated in the system for a two-wavelength technique. Both temperature and mole fraction can be inferred from the lineshape analysis using this approach. Additional high temperature spectroscopy research was conducted to reduce uncertainties in the scramjet application. The lasers are optical fiber coupled to ports at the combustor exit and in the nozzle region. The output from the two diode lasers were combined in a single fiber, and the resultant two-wavelength beam was subsequently split into four legs. Each leg was directed through 60 meters of optical fiber to four combustor exit locations for measurement of beam intensity after absorption by the water within the flow. Absorption results will be compared to 1D combustor analysis using RJPA and nozzle CFD computations as well as to data from a nozzle metric balance measuring thrust and integrated pressure measurements along the length of the nozzle. Assessment of its value as a combustor performance evaluation tool will be conducted.

Cavolowsky, John A.↗

NASA NTRSDate not supplied

Effect of Geometric Granularity on the Noise Signature of a Full-Scale Large Civil Transport Nose Landing Gear

Results from a comprehensive simulation campaign focused on characterizing the air-frame noise signature of a full-scale Boeing 777-300ER nose landing gear are presented. The as-flown, installed nose gear geometry was used to assess how accurately the selected computational methodology can predict far-field noise before extending the simulation approach to the complete B777-300ER aircraft in landing configuration. To facilitate direct comparisons with experimental data, the simulations were conducted for conditions matching those recorded for a flyby of the same aircraft over the ground-based phased microphone array used during the 2005 Quiet Technology Demonstrator II test. The far-field acoustic footprint of the nose landing gear was computed via a Ffowcs-Williams and Hawkings integral approach, with pressures on the model solid surface or flow quantities on a permeable data surface enclosing the gear used as input. A grid refinement study performed for the baseline gear con-figuration to establish the convergence behavior of the far-field spectrum indicated that the sound pressure levels had converged at frequencies slightly beyond 5 kHz for the finest spatial resolution attempted. To ascertain the effects of geometric granularity on far-field noise, simulations of a defeatured version of the nose gear were undertaken. Comparisons with fully-dressed gear results indicated that finer geometric details add 2–4 dB to the sound pressure levels at mid- to high-frequencies (800 Hz to 5 kHz), suggesting that for accurate noise prediction such details cannot be neglected.

airframe noise↗

DOE OSTI2020

Performance of an atomic mean-field spin–orbit approach within exact two-component theory for perturbative treatment of spin–orbit coupling

The paper reports development of an atomic mean-field (AMF) spin–orbit approach within the spin-free exact two-component theory in its one-electron variant (SFX2C-1e), a new relativistic quantum-chemical method for treating spin-orbit coupling in molecules. The effective one-electron spin–orbit integral matrix in the four-component representation is assembled as a direct sum of one-centre spin–orbit integral matrices with the mean-field two-electron contributions evaluated using atomic SFX2C-1e Hartree–Fock density matrices. It is then transformed into two-component representation using analytic SFX2C-1e energy derivative formulation. The resulting two-component spin–orbit integral matrix is by design suitable for use in perturbative calculations of spin–orbit coupling, treating SFX2C-1e wavefunctions as unperturbed states. The accuracy of the present AMF approach has been demonstrated using benchmark calculations of spin–orbit splittings for representative diatomic radicals at the equation-of-motion coupled-cluster singles and doubles level. In conclusion, to demonstrate the applicability and accuracy of the present perturbative spin–orbit scheme in calculations of challenging heavy-element containing systems, a thorough computational investigation of six low-lying electronic states of ThO+ is reported.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2023

Astronomical image time series classification using CONVolutional attENTION (ConvEntion)

Aims: The treatment of astronomical image time series has won increasing attention in recent years. Indeed, numerous surveys following up on transient objects are in progress or under construction, such as the Vera C. Rubin Observatory Legacy Survey for Space and Time (LSST), which is poised to produce huge amounts of these time series. The associated scientific topics are extensive, ranging from the study of objects in our galaxy to the observation of the most distant supernovae for measuring the expansion of the universe. With such a large amount of data available, the need for robust automatic tools to detect and classify celestial objects is growing steadily. Methods: This study is based on the assumption that astronomical images contain more information than light curves. In this paper, we propose a novel approach based on deep learning for classifying different types of space objects directly using images. We named our approach ConvEntion, which stands for CONVolutional attENTION. It is based on convolutions and transformers, which are new approaches for the treatment of astronomical image time series. Our solution integrates spatio-temporal features and can be applied to various types of image datasets with any number of bands. Results: In this work, we solved various problems the datasets tend to suffer from and we present new results for classifications using astronomical image time series with an increase in accuracy of 13%, compared to state-of-the-art approaches that use image time series, and a 12% increase, compared to approaches that use light curves.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

One of the open problems in scientific computing is the long-time integration of nonlinear stochastic partial differential equations (SPDEs), especially with arbitrary initial data. We address this problem by taking advantage of recent advances in scientific machine learning and the spectral dynamically orthogonal (DO) and borthogonal (BO) methods for representing stochastic processes. The recently introduced DO/BO methods reduce the SPDE to solving a system of deterministic PDEs and a system of stochastic ordinary differential equations. Specifically, we propose two new physics-informed neural networks (PINNs) for solving time-dependent SPDEs, namely the neural network (NN)-DO/BO methods. The proposed methods incorporate the DO/BO constraints into the loss function (along with the modal decomposition of the SPDE) with an implicit form instead of generating explicit expressions for the temporal derivatives of the DO/BO modes. Hence, the NN-DO/BO methods can overcome some of the drawbacks of the original DO/BO methods. For example, we do not need the assumption that the covariance matrix of the random coefficients is invertible as in the original DO method, and we can remove the assumption of no eigenvalue crossing as in the original BO method. Moreover, the NN-DO/BO methods can be used to solve time-dependent stochastic inverse problems with the same formulation and same computational complexity as for forward problems. Furthermore, we demonstrate the capability of the proposed methods via several numerical examples, namely: (1) A linear stochastic advection equation with deterministic initial condition: we obtain good results with the proposed methods, while the original DO/BO methods cannot be applied directly in this case. (2) Long-time integration of the stochastic Burgers' equation: we show the good performance of NN-DO/BO methods, especially the effectiveness of the NN-BO approach for such problems with many eigenvalue crossings during the whole time evolution, while the original BO method fails. (3) Nonlinear reaction diffusion equation: we consider both the forward problem and the inverse problems, including very noisy initial point values, to investigate the flexibility of the NN-DO/BO methods in handling inverse and mixed type problems. Taken together, these simulation results demonstrate that the NN-DO/BO methods can be employed to effectively quantify uncertainty propagation in a wide range of physical problems, but future work should address the efficiency issue of PINNs for forward problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Direct Air Capture Using Novel Structured Adsorbents (DE-FE0031959 Final Technical Report)

The objective of this project was to advance direct air capture (DAC) technology through a novel combination of a vacuum-temperature swing CO 2 adsorption process and structured adsorbent beds (SABs). The technical approach was to construct and operate an Integrated DAC System (IDS) at a test facility in Orange County, California. A 30 kilogram per day (kg/day) integrated field test unit was deployed into the field for testing, producing a concentrated CO 2 stream of at least 95% purity. A novel combination of DAC process and hardware with a transformational structured adsorbent laminate filter was fielded and tested at this site. The field testing also captured operational data on the novel process and material combination under real conditions. Data from this were used to advise techno-economic and life cycle analyses (TEA/LCA) of the technology. Despite the early development status and IDS aiming at field validation at TRL 5 rather than commercial scale operations, these analyses give valuable indications of this new technology route’s potential for cost reductions in DAC-based carbon dioxide removal. Climeworks and Svante are committed to further development of the technology route, including the realization of existing further cost reduction potential.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1997

Proceedings of the NASA First Wake Vortex Dynamic Spacing Workshop

A Government and Industry workshop on wake vortex dynamic spacing systems was conducted on May 13-15, 1997, at the NASA Langley Research Center. The purpose of the workshop was to disclose the status of ongoing NASA wake vortex R&D to the international community and to seek feedback on the direction of future work to assure an optimized research approach. Workshop sessions examined wake vortex characterization and physics, wake sensor technologies, aircraft/wake encounters, terminal area weather characterization and prediction, and wake vortex systems integration and implementation. A final workshop session surveyed the Government and Industry perspectives on the NASA research underway and related international wake vortex activities. This document contains the proceedings of the workshop including the presenters' slides, the discussion following each presentation, the wrap-up panel discussion, and the attendees' evaluation feedback.

Creduer, Leonard↗

NASA NTRS2004

Health Sensing Functions in Thermal Barrier Coatings Incorporating Rare-Earth-Doped Luminescent Sublayers

Great effort has been directed towards developing techniques to monitor the health of thermal barrier coatings (TBCs) that would detect the approach of safety-threatening conditions. An unconventional approach is presented here where health sensing functionality is integrated into the TBC itself by the incorporation of rare-earth-doped luminescent sublayers to monitor erosion as well as whether the TBC is maintaining the underlying substrate at a sufficiently low temperature. Erosion indication is demonstrated in electron-beam physical vapor deposited (EB-PVD) TBCs consisting of 7wt% yttria-stabilized zirconia (7YSZ) with europium-doped and terbium-doped sublayers. Multiple ingot deposition produced sharp boundaries between the doped sublayers without interrupting the columnar growth of the TBC. The TBC-coated specimens were subjected to alumina particle jet erosion, and the erosion depth was then indicated under ultraviolet illumination that excited easily visible luminescence characteristic of sublayer that was exposed by erosion. In addition, temperature measurements from a bottom-lying europium-doped sublayer in a TBC produced by multiple ingot EB-PVD were accomplished by measuring the temperature-dependent decay time from the 606 nm wavelength emission excited in that sublayer with a 532 nm wavelength laser that was selected for its close match to one of the europium excitation wavelengths as well as being at a wavelength where the TBC is relatively transparent. It is proposed the low dopant levels and absence of interruption of the TBC columnar growth allow the addition of the erosion and temperature sensing functions with minimal effects on TBC performance.

Eldridge, J. I.↗

NASA NTRS2012

A 2-Micron Pulsed Integrated Path Differential Absorption Lidar Development For Atmospheric CO2 Concentration Measurements

A 2-micron pulsed, Integrated Path Differential Absorption (IPDA) lidar instrument for ground and airborne atmospheric CO2 concentration measurements via direct detection method is being developed at NASA Langley Research Center. This instrument will provide an alternate approach to measure atmospheric CO2 concentrations with significant advantages. A high energy pulsed approach provides high-precision measurement capability by having high signal-to-noise level and unambiguously eliminates the contamination from aerosols and clouds that can bias the IPDA measurement.

Yu, Jirong↗

NASA NTRS2012

High Energy 2-Micron Solid-State Laser Transmitter for NASA's Airborne CO2 Measurements

Singh, Upendra N.↗

NASA NTRS2016

A Robust Method to Integrate End-to-End Mission Architecture Optimization Tools

End-to-end mission simulations include multiple phases of flight. For example, an end-to-end Mars mission simulation may include launch from Earth, interplanetary transit to Mars and entry, descent and landing. Each phase of flight is optimized to meet specified constraints and often depend on and impact subsequent phases. The design and optimization tools and methodologies used to combine different aspects of end-to-end framework and their impact on mission planning are presented. This work focuses on a robust implementation of a Multidisciplinary Design Analysis and Optimization (MDAO) method that offers the flexibility to quickly adapt to changing mission design requirements. Different simulations tailored to the liftoff, ascent, and atmospheric entry phases of a trajectory are integrated and optimized in the MDAO program Isight, which provides the user a graphical interface to link simulation inputs and outputs. This approach provides many advantages to mission planners, as it is easily adapted to different mission scenarios and can improve the understanding of the integrated system performance within a particular mission configuration. A Mars direct entry mission using the Space Launch System (SLS) is presented as a generic end-to-end case study. For the given launch period, the SLS launch performance is traded for improved orbit geometry alignment, resulting in an optimized a net payload that is comparable to that in the SLS Mission Planner's Guide.

Lugo, Rafael↗

DOE OSTI2025

ACCELERATED DEPLOYMENT OF NOVEL MATERIALS BASED ON RELIABILITY INTEGRITY MANAGEMENT USING CUMULATIVE DAMAGE MODELING

There is currently no widely agreed, detailed general method for licensing a novel plant incorporating novel materials (or materials being deployed in novel environments); in many such situations, there are no directly applicable engineering code cases for decision-makers (including regulators) to rely on. This paper discusses a framework for solving this problem that is based on the Reliability and Integrity Management (RIM) approach delineated in ASME BPVC Section XI Division 2. NRC Regulatory Guide 1.246, Rev. 0, endorses, with conditions, the subject portion of the 2019 ASME Code. The proposed framework is meant to support development of a licensing case by addressing certain remaining technical challenges. The framework discussed here is compatible with the Licensing Modernization Project, but applying it in a specific case will call for advances in the state of practice, if not the state of the art. The RIM approach calls for applicants to (a) allocate reliability targets to plant structures, systems, and components (SSCs), (b) show that they are able to relate the currently observed physical condition of each SSC in the program to its failure probability well enough to determine whether the target reliability allocations are being satisfied, allowing for uncertainty related to the novelty of the materials/designs/operating environments, and (c) be able to demonstrate that the proposed program of surveillances will reliably detect unacceptable degradation of an SSC before SSC failure occurs. A modeling approach potentially applicable to item (b), based on cumulative damage modeling rather than failure rates, is briefly illustrated.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗