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DOE OSTI2023

Accretion disks, quasars and cosmology: meandering towards understanding

Abstract As Setti and Woltjer noted back in 1973, one can use quasars to construct the Hubble diagram; however, the actual application of the idea was not that straightforward. It took years to implement the proposition successfully. Most ways to employ quasars for cosmology now require an advanced understanding of their structure, step by step. We briefly review this progress, with unavoidable personal biases, and concentrate on bright unobscured sources. We will mention the problem of the gas flow character close to the innermost stable circular orbit near the black hole, as discussed five decades ago. This problem later led to the development of the slim disk scenario and is recently revived in the context of Magnetically Arrested Disks (MAD) and Standard and Normal Evolution (SANE) models. We also discuss the hot or warm corona issue, which is still under debate and complicates the analysis of X-ray reflection. We present the scenario of the formation of the low ionization part of the Broad Line Region as a failed wind powered by radiation pressure acting on dust (Failed Radiatively Driven Dusty Outflow – FRADO). Next, we examine the cosmological constraints currently achievable with quasars, primarily concentrating on light echo methods (continuum time delays and spectral-line time delays to the continuum) that are (or should be) incorporating the progress mentioned above. Finally, we briefly discuss prospects in this lively subject area.

Astronomy & Astrophysics↗

DOE OSTI2020

Assessment of Survey Results from Advanced Reactor Industry Domain Experts on Nonlinear Soil-Structure Interaction Analysis Software Verification and Validation

The seismic load case has a significant impact on the design and cost of nuclear power plants. Given the need to substantially reduce cost, advanced reactor designers are looking to leverage numerical tools that enable seismic analysis of an integrated vessel/support/structure/soil system. Modern nonlinear analysis tools provide a solution, capturing dynamic coupling between components (including soil-structure interaction (SSI)) concurrent with nonlinear behavior in one or more parts of the system. Although these methods have a rich history of technical development and implementation, software quality assurance (SQA) following nuclear industry standards remains a significant burden for those wishing to adopt such methods for advanced reactor design and licensing. To reduce the SQA burden, this project will develop the guidance for SQA verification and validation (V&V) of coupled nonlinear SSI analysis tools, to include a test matrix of software features and test problems to support commercial grade dedication (CGD). The guidance is intended to be technology-neutral: supporting designers of all advanced reactors. To maximize the value of the project to reactor designers, the project team performed focused surveys of and interviews with advanced reactor designers. Additionally, the project surveyed members of the broader industry involved in reactor design and licensing. The aggregated industry feedback consists of written survey responses, live polling responses, focused interviews, and informal feedback provided after outreach presentations, collectively referred to as “survey results”. Herein, the survey results are reported, reviewed, and assessed to inform follow-on project activities. The survey results confirmed the familiarity of the industry with the coupled nonlinear SSI analysis. They also affirm the project need based upon the expressed intent to (1) incorporate nonlinear features and (2) pursue the coupled nonlinear SSI analysis to reduce seismic demands and construction costs. All reactor designers indicated their intent to incorporate two or more nonlinear features, and all reactor designer respondents opined that the coupled nonlinear SSI analysis would allow for the optimization of the reactor design and construction. However, the programmatic challenges, whether real or perceived, present a significant barrier to reactor designers. The barrier most commonly identified by the reactor designer population was regulatory risk, with 70% citing this as a reason not to pursue the approach. The perceived regulatory risk identified by the reactor designers underscores the importance of regulator engagement and dialogue in this project. Additionally, half of the reactor designers identified cost and lack of guidance as a deterrent. The survey results also provide insights to tailor specific aspects of the guidance document and test matrix. The project plans to prepare both a formal referenceable guidance document and a collaborative, web-based test matrix and problem set. The project will focus on more complete test problem definitions for the prioritized nonlinear features over shallower problem descriptions for a larger set of features. The nonlinearities prioritized as high based upon survey feedback include fluid-structure interaction and seismic isolation and energy dissipation devices. The nonlinearities prioritized as intermediate include nonlinear geomaterials, nonlinear concrete, nonlinear steel, and interface/contact nonlinearity. Deep embedment and the associated nonlinear phenomena are assigned the lowest priority based upon survey feedback.

42 ENGINEERING↗

DOE OSTI2024

Machine Learning-Driven Reliability Estimation of PV Inverters Considering Alert-Ambient Variability

Weather-induced spatio-temporal degradation limits outdoor PV inverter lifetime and reliability, necessitating advanced data analysis. This study employs a top-down, data-driven approach utilizing multiple machine learning (ML) algorithms to estimate inverter reliability in a 1.4 MW PV power plant, considering factors such as irradiance, humidity, temperature, time of day, and weather conditions. An extensive alert dataset from 17 identical inverters, including alert types, propagation, and frequency, reveals significant correlations with environmental factors and inverter output power, enabling the construction of a performance reliability model. Dual-stage supervised-ML models are evaluated for accuracy, with the ‘classification-regression’ model by an artificial neural network (ANN) tested on the averaged “Alert-Ambient” dataset, which is outperformed by ‘clustering-regression’ models using random forest (RF) and K-Nearest Neighbors (KNN) on individual inverter datasets. K-means clustering applies principal component analysis to reduce dimensions, achieving improved accuracy beyond the 80% achieved by ANN on the averaged dataset. Second-stage regression estimates inverter reliability with a mean square error of 0.0195 on the averaged dataset and as low as 0.002 on individual inverter datasets using RF. Furthermore, these findings highlight the method's suitability for estimating PV inverter output reliability under ambient conditions, essential for digital twin development and related applications.

14 SOLAR ENERGY↗

NASA NTRSDate not supplied

NASA Earth Systems Digital Twins (ESDT)

"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."

Earth Science Remote Sensing; Information Systems↗

NASA NTRS1995

Integrated design and manufacturing for the high speed civil transport (a combined aerodynamics/propulsion optimization study)

This report documents the efforts of a Georgia Tech High Speed Civil Transport (HSCT) aerospace student design team in completing a design methodology demonstration under NASA's Advanced Design Program (ADP). Aerodynamic and propulsion analyses are integrated into the synthesis code FLOPS in order to improve its prediction accuracy. Executing the integrated product and process development (IPPD) methodology proposed at the Aerospace Systems Design Laboratory (ASDL), an improved sizing process is described followed by a combined aero-propulsion optimization, where the objective function, average yield per revenue passenger mile ($/RPM), is constrained by flight stability, noise, approach speed, and field length restrictions. Primary goals include successful demonstration of the application of the response surface methodolgy (RSM) to parameter design, introduction to higher fidelity disciplinary analysis than normally feasible at the conceptual and early preliminary level, and investigations of relationships between aerodynamic and propulsion design parameters and their effect on the objective function, $/RPM. A unique approach to aircraft synthesis is developed in which statistical methods, specifically design of experiments and the RSM, are used to more efficiently search the design space for optimum configurations. In particular, two uses of these techniques are demonstrated. First, response model equations are formed which represent complex analysis in the form of a regression polynomial. Next, a second regression equation is constructed, not for modeling purposes, but instead for the purpose of optimization at the system level. Such an optimization problem with the given tools normally would be difficult due to the need for hard connections between the various complex codes involved. The statistical methodology presents an alternative and is demonstrated via an example of aerodynamic modeling and planform optimization for a HSCT.

Baecher, Juergen↗

DOE OSTI2020

Integrating field observations and process-based modeling to predict watershed water quality under environmental perturbations

Watersheds play a critical role in supplying water resources needed for human use and ecosystem health. Understanding and predicting how, when, and where changes in the quantity and quality of water resources occur under different environmental stresses including extreme events is crucial for sustainable management of water resources under a changing environment. However, few studies have attempted to quantify or identify the factors and process interactions controlling the impact of extreme events across water-shed systems. Only few large-scale studies include coordinated monitoring and modeling efforts, which limits our ability to assess the large-scale impact of extreme events on water supply and quality. Methods are lacking to propagate uncertainty in process understanding through an integrated hydro-biogeochemical model framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformative advances in characterization technologies from high-resolution mass spectrometry to airborne and satellite-based remote sensing. There are consequent risks to our nations water security and to human and ecosystem health that may become exacerbated with the increasing frequency of extreme events that is projected for the coming decades. This paper reviews the current status of watershed science for both water quantity and quality and identifies critical gaps in our current knowledge and modeling capability in addressing the emergent needs in predicting watershed hydrologic and biogeochemical responses (i.e., water quantity and quality) under natural and anthropogenic perturbations. We highlight the need to (1) understand how environmental perturbations including extreme events like floods and droughts propagate through watershed systems and assess their short- and long-term impacts on watershed biogeochemistry, water quality and their recovery pathways; (2) develop and improve a watershed water quality model that reflects the state of scientific understanding gained from observations; and (3) construct a data-model fusion system for watershed characterization, process identification, and mechanistic model parameterization. A large base of modeling, monitoring and data capabilities have been built by various federal government agencies given the relevance of water to their critical missions. An emerging need is to build an integrated national capability for watershed water availability and quality that can address water-related missions across multiple federal agencies.

13 HYDRO ENERGY↗

DOE OSTI2026

Multi-system analysis of offshore geologic carbon storage: a review of open-source data science solutions

Geologic carbon storage projects are maturing worldwide and the footprint of deployment in the offshore is expanding. At present, there are ten projects in operation or that have been completed, more than 50 in construction and development, and dozens of characterization studies completed or underway. Offshore geologic carbon storage offers potential benefits over onshore geologic carbon storage. These offshore projects are generally remote in location, distant from population centers, and avoid complicated pore space rights while having abundant prospective storage potential. Some offshore fields targeted for carbon storage have comparatively fewer prior borehole penetrations except for areas that have been explored for petroleum production, minimizing potential issues such as pressure interference and infrastructure impacts. Yet offshore geologic carbon storage projects face distinctive technical and economic challenges, such as seafloor geohazards (e.g., seabed instability), expensive maritime transport, and meteorological-oceanographic conditions that can damage infrastructure and impact operations. Analytical capabilities and improved computational speeds have advanced engineering, earth and energy sciences in the wake of the arrival of modern data science over the last decade. These advancements have created an opportunity for integrated, multi-systems modeling approaches utilizing artificial intelligence and machine learning that are no longer limited by computational issues. Analytical tools developed alongside this advancement in data science can be leveraged to calibrate the potential advantages and challenges of carbon storage operations in the offshore. New methods and approaches that incorporate data science to analyze multiple aspects of engineered and natural systems can provide insights that complement the characterization and onsite engineering that traditional commercial and operational software addresses. These new methods and approaches can potentially improve the outcome of energy operations and carbon storage. Providing multi-system, science-driven data analytics enhances the knowledge base that offshore developers, operators, and regulatory bodies may draw from to improve offshore site selection and operational efficiency. Here, we provide a brief synopsis of geologic carbon storage efforts to date, an overview of the engineered and natural systems involved in offshore geologic carbon storage, and a review of publicly available, open-source, offshore and/or carbon storage related data- and science-driven tools developed by 2010 or later that are suitable for screening and assessing regions for offshore geologic carbon storage.

artificial intelligence↗

NASA NTRS1960

Experimental Smoke and Electromagnetic Analog Study of Induced Flow Field About a Model Rotor in Steady Flight Within Ground Effect

Hovering and steady low-speed forward-flight tests were run on a 4-foot-diameter rotor at a ground height of 1 rotor radius. The two blades had a 2 to 1 taper ratio and were mounted in a see-saw hub. The solidity ratio was 0.05. Measurements were made of the rotor rpm, collective pitch, and forward-flight velocity. Smoke was introduced into the tip vortex and the resulting vortex pattern was photographed from two positions. Using the data obtained from these photographs, wire models of the tip vortex configurations were constructed and the distribution of the normal component of induced velocity at the blade feathering axis that is associated with these tip vortex configurations was experimentally determined at 450 increments in azimuth position from this electromagnetic analog. Three steady-state conditions were analyzed. The first was hovering flight; the second, a flight velocity just under the wake "tuck under" speed; and the third, a flight velocity just above this speed. These corresponded to advance ratios of 0, 0.022, and 0.030 (or ratios of forward velocity to calculated hovering induced velocity of approximately 0, 0.48, and 0.65), respectively, for the model test rotor. Cross sections of the wake at 450 intervals in azimuth angle as determined from the path of the tip vortex are presented graphically for all three cases. The nondimensional normal component of the induced velocity that is associated with the tip vortex as determined by an electromagnetic analog at 450 increments in azimuth position and at the blade feathering axis is presented graphically. It is shown that the mean value of this component of the induced velocity is appreciably less after tuck-under than before. It is concluded that this method yields results of engineering accuracy and is a very useful means of studying vortex fields.

Gray, Robin B.↗

DOE OSTI2020

Advancing reliability assessments of photovoltaic modules and materials using combined-accelerated stress testing

Previously undiscovered failure modes in photovoltaic (PV) modules continue to emerge in field installations despite passing protocols for design qualification and quality assurance. Failure to detect these modes prior to widespread use could be attributed to the limitations of present-day standard accelerated stress tests (ASTs), which are primarily designed to identify known degradation or failure modes at the time of development by applying simultaneous or sequential stress factors (usually two at most). Here, we introduce an accelerated testing method known as the combined-accelerated stress test (C-AST), which simultaneously combines multiple stress factors of the natural environment. Simultaneous combination of multiple stress factors allows for improved identification of failure modes with better ability to detect modes not known a priori. A demonstration experiment was conducted that reproduced the field-observed cracking of polyamide- (PA-) and polyvinylidene fluoride (PVDF)–based backsheet films, a failure mode that was not detected by current design qualification and quality assurance testing requirements. In this work, a two-phase testing protocol was implemented. The first cycle (“Tropical”) is a predominantly high-humidity and high-temperature test designed to replicate harsh tropical climates. The second cycle (“Multi-season”) was designed to replicate drier and more temperate conditions found in continental or desert climates. Testing was conducted on 2 × 2-cell crystalline-silicon cell miniature modules constructed with both ultraviolet (UV)–transmitting and UV-blocking encapsulants. Cracking failures were observed within a cumulative 120 days of the Tropical condition for one of the PA-based backsheets and after 84 days of Tropical cycle followed by 42 days of the Multi-season cycle for the PVDF-based backsheet, which are both consistent with failures seen in fielded modules. In addition to backsheet cracking, degradation modes were observed including solder/interconnect fatigue, various light-induced degradation modes, backsheet delamination, discoloration, corrosion, and cell cracking. The ability to simultaneously apply multiple stress factors may allow many of the test sequences within the standardized design qualification procedure to be performed using a single test setup.

14 SOLAR ENERGY↗

DOE OSTI2024

Incorporating Coverage-Dependent Reaction Barriers into First-Principles-Based Microkinetic Models: Approaches and Challenges

Mean-field microkinetic models (MKMs) are appealing for their relatively facile construction, computational tractability, and high-throughput catalyst screening capabilities. As such, they will continue to be a valuable tool for materials design in heterogeneous catalysis even as the field aims to describe more complex systems. Numerous prior reports have provided the groundwork for constructing first-principles-based MKMs, including the analysis of strategies for incorporating lateral interactions into thermodynamic parameters (e.g., adsorption energies). Yet, there remains a need for concerted dialogue on methods for calculating and incorporating coverage-dependent kinetic parameters into MKMs. In this Perspective, we assess strategies for doing so, including the corresponding key physical implications and computational challenges. Here, we emphasize that decoupling thermodynamic and kinetic parameters within MKMs can violate thermodynamic consistency and risk unphysical solutions. For some reactions and catalyst materials, scaling relationships can predict coverage-dependent activation energies, but there are several exceptions evident in the literature, indicating that this approach is not universally applicable and that the field could benefit from research aimed at elucidating the limitations. Conducting high-coverage transition state searches is a rigorous but computationally costly strategy, and the effects of various methods for mitigating this cost on resulting energetics have yet to be broadly explored and validated. The goal of this Perspective is to generate discussion on and inspire focused research into the physical relevance of approaches for describing coverage-dependent reaction barriers in MKMs, including the development of computationally tractable methodologies, to advance the applicability of MKMs across diverse reaction chemistries and conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Molten Salt Corrosion Tests of Additively Manufactured Stainless Steel 316H

Molten salt reactors (MSRs) have drawn considerable interest due to their favorable safety features, high thermal efficiency, and compatibility with different fuel cycles. Yet, the success of MSRs hinges critically on the performance of structural materials to be used in these aggressive molten salt environments, where corrosion and material compatibility remain primary challenges to long-term reliability. Additively manufactured (AM) nuclear structural materials prompt the use of novel geometries and compositions to enhance material performance and reduce costs of constructing MSRs. The rapid solidification conditions inherent to AM processing impart distinctive microstructural features, including cellular sub-structures, dislocation densities, residual stress, and oxide inclusions, which can influence material performance in MSR components. While the mechanical properties of AM stainless steels have been widely studied, their corrosion behavior, particularly in molten salt environments, has received far less attention. Addressing these needs, the Advanced Materials and Manufacturing Technologies (AMMT) program provides a framework for systematically evaluating how unique microstructures produced by AM processes influence the performance of these materials in these demanding environments and for developing reproducible testing workflows that can support future code qualification efforts and standards development. Bridging this knowledge gap is essential for assessing the viability of AM alloys in MSRs and informing qualification strategies. A further challenge is the absence of standardized protocols for molten salt corrosion testing. Accordingly, this report provides an account of the corrosion evaluation of AM 316H stainless steel in NaCl 2 -MgCl 2 molten salt at 550 °C, with exposure times of 100 and 500 hours. It documents the experimental procedures implemented under the AMMT program, including salt preparation, exposure protocols, and post-test characterization methods, to establish reproducibility and transparency. Importantly, the study examines AM 316H samples in the as-fabricated condition, directly reflecting the surface state most relevant to engineering applications, and compares their behavior to machine-cut surfaces. Overall, preliminary evaluations have noted that surface conditions (e.g. morphology, contamination, etc.) have a noticeable impact on the corrosion resiliency. The impact of the corrosion is difficult to detect at 100h, unless, in the case of AM 316H, the specimen surface is decontaminated. After 500 h, as-fabricated surfaces of AM and wrought 316H display evidence of general versus preferential corrosion attack, respectively. Both AM and wrought 316H machine-cut surfaces exhibit a continuous Cr depletion zone, evident of general corrosion. While the estimated extent of corrosion appears within the same order of magnitude regardless of the surface condition, it is apparent that more predictable behavior is observed on machine-cut surfaces. Nonetheless, further investigation is necessary to fully elucidate the corrosion mechanism under these conditions.

36 - MATERIALS SCIENCE↗

NASA NTRS2005

Heat Transfer and Thermal Stability Research for Advanced Hydrocarbon Fuel Technologies

In recent years there has been increased interest in the development of a new generation of high performance boost rocket engines. These efforts, which will represent a substantial advancement in boost engine technology over that developed for the Space Shuttle Main Engines in the early 1970s, are being pursued both at NASA and the United States Air Force. NASA, under its Space Launch Initiative s Next Generation Launch Technology Program, is investigating the feasibility of developing a highly reliable, long-life, liquid oxygen/kerosene (RP-1) rocket engine for launch vehicles. One of the top technical risks to any engine program employing hydrocarbon fuels is the potential for fuel thermal stability and material compatibility problems to occur under the high-pressure, high-temperature conditions required for regenerative fuel cooling of the engine combustion chamber and nozzle. Decreased heat transfer due to carbon deposits forming on wetted fuel components, corrosion of materials common in engine construction (copper based alloys), and corrosion induced pressure drop increases have all been observed in laboratory tests simulating rocket engine cooling channels. To mitigate these risks, the knowledge of how these fuels behave in high temperature environments must be obtained. Currently, due to the complexity of the physical and chemical process occurring, the only way to accomplish this is empirically. Heated tube testing is a well-established method of experimentally determining the thermal stability and heat transfer characteristics of hydrocarbon fuels. The popularity of this method stems from the low cost incurred in testing when compared to hot fire engine tests, the ability to have greater control over experimental conditions, and the accessibility of the test section, facilitating easy instrumentation. These benefits make heated tube testing the best alternative to hot fire engine testing for thermal stability and heat transfer research. This investigation used the Heated Tube Facility at the NASA Glenn Research Center to perform a thermal stability and heat transfer characterization of RP-1 in an environment simulating that of a high chamber pressure, regenerative cooled rocket engine. The first step in the research was to investigate the carbon deposition process of previous heated tube experiments by performing scanning electron microscopic analysis in conjunction with energy dispersive spectroscopy on the tube sections. This analysis gave insight into the carbon deposition process and the effect that test conditions played in the formation of deleterious coke. Furthermore, several different formations were observed and noted. One other crucial finding of this investigation was that in sulfur containing hydrocarbon fuels, the interaction of the sulfur components with copper based wall materials presented a significant corrosion problem. This problem in many cases was more life limiting than those posed by the carbon deposition process. The results of this microscopic analysis was detailed and presented at the December 2003 JANNAF Air-Breathing Propulsion Meeting as a Materials Compatibility and Thermal Stability Analysis of common Hydrocarbon Fuels (reference 1).

DeWitt, Kenneth↗

DOE OSTI2022

Transferability of data-driven, many-body models for CO 2 simulations in the vapor and liquid phases

Here, extending on the previous work by Riera et al. [J. Chem. Theory Comput. 16, 2246–2257 (2020)], we introduce a second generation family of data-driven many-body MB-nrg models for CO 2 and systematically assess how the strength and anisotropy of the CO 2 –CO 2 interactions affect the models’ ability to predict vapor, liquid, and vapor–liquid equilibrium properties. Building upon the many-body expansion formalism, we construct a series of MB-nrg models by fitting one-body and two-body reference energies calculated at the coupled cluster level of theory for large monomer and dimer training sets. Advancing from the first generation models, we employ the charge model 5 scheme to determine the atomic charges and systematically scale the two-body energies to obtain more accurate descriptions of vapor, liquid, and vapor–liquid equilibrium properties. Challenges in model construction arise due to the anisotropic nature and small magnitude of the interaction energies in CO 2 , calling for the necessity of highly accurate descriptions of the multidimensional energy landscape of liquid CO 2 . These findings emphasize the key role played by the training set quality in the development of transferable, data-driven models, which, accurately representing high-dimensional many-body effects, can enable predictive computer simulations of molecular fluids across the entire phase diagram.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Light Energy Transduction in Green Sulfur Bacteria

Green sulfur bacteria (GSB) are exquisitely adapted for growth at extraordinarily low light intensities. They are important primary producers of biomass in many anoxic environments, and they contribute significantly to the biogeochemical cycling of carbon, nitrogen, and sulfur on Earth. Green bacteria more generally share the property of using chlorosomes for light-harvesting, and these unusual organelles have many unique features. These include the presence of a monolayer lipid-protein envelope, self-assembling bacteriochlorophylls (BChl) in which pigment-pigment interactions predominate, and the presence of redox components ([2Fe-2S] ferredoxins and quinones) that play a role in regulating excitation energy transfer to the type-1 homodimeric reaction centers. The reaction centers of GSB are related to Photosystem I of cyanobacteria and higher plants but also exhibit several unique structural and functional features. The long-term objectives of this research program are to understand the structure, functions, and biogenesis of the chlorosomes, reaction centers, and electron transport chains that carry out the photochemical transduction of light energy into chemical energy in the model green sulfur bacterium, Chlorobaculum (formerly Chlorobium) tepidum. Over a period of 26 years, we characterized chlorosomes in detail. We identified the proteins in the chlorosome envelopes of diverse organisms, identified the nearest neighbors of those proteins, and characterized the chlorosomes of mutant strains lacking one to five of these proteins. After the genome sequence of Cba. tepidum became available, we identified all genes encoding enzymes for BChl a , BChl c/d/e/ƒ , and Chl a biosynthesis Cba. tepidum . We additionally identified all genes encoding enzymes for carotenoid biosynthesis. By constructing a bchQRU mutant strain that produces [Et, Me]-BChl d , together with collaborators who are specialists in solid-state NMR and cryo-electron microscopy, we solved the structure of the BChls in chlorosomes. Using similar methods and chlorosomes containing [Et, Me]-BChl c , we then showed that alternative structures were possible using the same syn-anti BChl dimer. The structures were refined by introducing spectroscopic data from single-chlorosome measurements. Over the course of this project, we sequenced the genomes of approximately twenty GSB strains, which provided important information for comparative analyses. Through analyses of metagenomic data from Mushroom and Octopus Springs in Yellowstone National Park, we identified a novel chlorophototroph belonging to the phylum Acidobacteriota. We successfully isolated an axenic culture of this organism. We characterized the photosynthetic apparatus of this bacterium, named Chloracidobacterium thermophilum, in significant detail, in particular its type-1, homodimeric reaction centers. Surprisingly, these reaction centers contain three types of Chls, BChl a , Chl a , and Zn-BChl a' . We showed that a dimer of Zn-BChl a' is the primary donor and Chl a the primary acceptor of electrons in this reaction center by using advanced spectroscopic techniques. We isolated eight additional strains of Chloracidobacterium spp. from Mushroom Spring and Rupite hot springs in Bulgaria. Comparative genomes showed that these represent three species, Cab. thermophilum , Cab. aggregatum , and Cab. validum . By applying comparative genomics, genetic, biochemical biophysical and physiological approaches to study green bacteria, we produced a wealth of new information about the remarkable light-harvesting and energy transduction capabilities of these poorly characterized microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2008

Performance Basis for Airborne Separation

Emerging applications of Airborne Separation Assistance System (ASAS) technologies make possible new and powerful methods in Air Traffic Management (ATM) that may significantly improve the system-level performance of operations in the future ATM system. These applications typically involve the aircraft managing certain components of its Four Dimensional (4D) trajectory within the degrees of freedom defined by a set of operational constraints negotiated with the Air Navigation Service Provider. It is hypothesized that reliable individual performance by many aircraft will translate into higher total system-level performance. To actually realize this improvement, the new capabilities must be attracted to high demand and complexity regions where high ATM performance is critical. Operational approval for use in such environments will require participating aircraft to be certified to rigorous and appropriate performance standards. Currently, no formal basis exists for defining these standards. This paper provides a context for defining the performance basis for 4D-ASAS operations. The trajectory constraints to be met by the aircraft are defined, categorized, and assessed for performance requirements. A proposed extension of the existing Required Navigation Performance (RNP) construct into a dynamic standard (Dynamic RNP) is outlined. Sample data is presented from an ongoing high-fidelity batch simulation series that is characterizing the performance of an advanced 4D-ASAS application. Data of this type will contribute to the evaluation and validation of the proposed performance basis.

Wing, David J.↗

DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗

DOE OSTI2024

Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors. This evaluation is performed using ground truth data, obtained by measuring the lane positions and transforming them into pixel coordinates. The performance of each method is assessed using the statistical R2 score, indicating the correlation between the detected lane lines and the ground truth. The results show that the U-Net camera-based method exhibits limitations in accurately detecting and aligning the lane lines, particularly in challenging scenarios. However, the radar-based lane detection method demonstrates a strong correlation with the ground truth which implies that the use of this sensor may improve current reliability issues from conventional camera lane detection approach. Furthermore, the study highlights the limitations of the U-Net model for camera lane detection, especially in scenarios with sun glare. This study shows that infrastructure-based radar retro-reflectors can improve autonomous vehicle lane detection reliability. The integration of different sensor modalities and the development of advanced computer vision algorithms are crucial for improving the accuracy, reliability, and energy efficiency of lane detection systems. Addressing these challenges contributes to the advancement of autonomous vehicles and the realization of safer and more efficient transportation systems.

Brown, Nicolas E.↗

DOE OSTI2021

Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ΔR. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

54 ENVIRONMENTAL SCIENCES↗