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At least 829 records · Page 46

Time dependent supervisory control update with FARM using rolling window

This report describes improvements to the Feasible Actuator Range Modifier (FARM) component of the RAVEN-based HYBRID framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON plug-in that solves the power dispatch problem. The solution to the dispatch problem involves economically optimal dispatches that satisfy limits on production variables and their rates of variation (explicit constraints) as well as process variables tied to the service life of equipment (implicit constraints). FARM serves to validate or confirm that a HERON solution for explicit constraints also satisfies the implicit constraints. FARM-alpha was released by Argonne National Laboratory in January 2021 followed by FARM-Beta in January 2022 with the latter providing increased flexibility for the user. In this report, FARM-Gamma, the latest version of the code, is described. The major improvement is the implementation of a system identification algorithm based on the Dynamic Mode Decomposition with Control (DMDc) coupled with a “Rolling Window” scheme that allows obtaining linear time-varying state-space models. This feature equips FARM with the most accurate approximation of system dynamics, and it relieves the user from the burden of performing an exhaustive off-line characterization of the dynamics. FARM-Gamma capabilities are assessed by solving the power dispatch problem for a representative IES unit. The simulation times corresponding to the different releases are estimated and compared. These values capture the increasing computational burden of the successively higher fidelity state-space models adopted by FARM-Alpha, FARM-Beta and FARM-Gamma. The code implementation provides significant flexibility, i.e., the user can always select the most suitable version of FARM according to the problem to be solved and the available computational resources. It is anticipated that FARM will play a role in addressing several future IES applications. We outline how it can support the coordinated management and safe operation of a nuclear plant coupled to industrial processes to produce hydrogen and synfuels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Achieving Unprecedented CO 2 Utilization InCO 2 Concrete™: System Design, Product Development and Process Demonstration

Anthropogenic sources of carbon dioxide are generated from a number of sources, but the key among these are ordinary Portland cement (OPC) production and combustion of fossil fuels. Cement production is the largest global CO 2 source from the mineral decomposition of carbonates. This is due to the clinkering process whereby limestone (mainly consisting of CaCO 3 ) is decomposed into CaO and CO 2 , and combined with silica rich clays at high temperatures to form clinkers (i.e. the four key minerals that comprise cement). The high temperature range of 1400 – 1550°C required for this process accounts for up to 60% of the generated CO 2 from cement production. Combination of the limestone decomposition and thermal requirements of the clinkering process causes cement production to contribute 8-9% of annual global CO 2 emissions. Combustion of fossil fuels (coal, oil and gas) was shown to contribute a much larger portion of global CO 2 emissions. As of 2018, combustion of fossil fuels accounted for 65% of global CO 2 , where 41% was derived from stationary sources for electricity and heat generation and the other 24% was related to transport. To reduce these contributions, key steps forward in CO 2 utilization technologies are required. Therefore, a CO 2 mineralization technology (CO 2 mineralization concrete) to reduce the OPC content in concrete, while utilizing flue gas emissions from fossil fuel combustion has been developed to address both areas simultaneously. This Reversa™ technology utilizes low-carbon cementation agents produced by in situ CO 2 mineralization (“mineral carbonation reactions”) to offer a promising alternative to OPC. CO 2 mineralization relies upon the reaction of dissolved CO 2 with inorganic alkaline reactants to precipitate mineral carbonates (e.g., CaCO 3 ), which bind proximate particles and achieve cementation. Herein, a concrete green body, which is composed of a mixture of binder, water, and mineral aggregates, is exposed to CO 2 borne in industrial flue gas streams. This manner of CO 2 mineralization allows the production of construction components that feature equivalent engineering attributes as their OPC-based counterparts while featuring a much smaller embodied carbon intensity (eCI). The purpose of this project is to demonstrate the feasibility of the Reversa process evolving from a TRL-3 technology at the bench-scale up to TRL-6 technology at the pilot-scale. The reliability of the Reversa technology was tested to prove the effective production of three standard industrial concrete products selected during the course of the project. The results detailed herein will demonstrate the evolution of this technology to the industrial scale. The culmination of this work resulted in 9 production runs completed at the National Carbon Capture Center (NCCC), Wilsonville, AL, using natural gas (NG) flue gas as the CO 2 source. Over the course of the production runs at NCCC, the CO 2 utilization as a function of time, 24-h CO 2 uptake, electricity usage, and 28-d net area compressive strength recorded for each run. Collection of this data will be used to determine the success of the demonstration goals: (1) achieving in excess of 0.2gCO 2 /g reactant , (2) achieving greater than 50% reduction in global warming potential compared to standard produced units, and (3) ensuring compliance of carbonated concrete with industry standard specifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A conceptual design study of point focusing thin-film solar concentrators

Candidates for reflector panel design concepts, including materials and configurations, were identified. The large list of candidates was screened and reduced to the five most promising ones. Cost and technical factors were used in making the final choices for the panel conceptual design, which was a stiffened steel skin substrate with a bonded, acrylic overcoated, aluminized polyester film reflective surface. Computer simulations were run for the concentrator optics using the selected panel design, and experimentally determined specularity and reflectivity values. Intercept factor curves and energy to the aperture curves were produced. These curves indicate that surface errors of 2 mrad (milliradians) or less would be required to capture the desired energy for a Brayton cycle 816 C case. Two test panels were fabricated to demonstrate manufacturability and optically tested for surface error. Surface errors in the range of 1.75 mrad and 2.2 mrad were measured.

Source record↗

Development of large, horizontal-axis wind turbines

A program to develop large, horizontal-axis wind turbines is discussed. The program is directed toward developing the technology for safe, reliable, environmentally acceptable large wind turbines that can generate a significant amount of electricity at costs competitive with those of conventional electricity-generating systems. In addition, these large wind turbines must be fully compatible with electric utility operations and interface requirements. Several ongoing projects in large-wind-turbine development are directed toward meeting the technology requirements for utility applications. The machines based on first-generation technology (Mod-OA and Mod-1) successfully completed their planned periods of experimental operation in June, 1982. The second-generation machines (Mod-2) are in operation at selected utility sites. A third-generation machine (Mod-5) is under contract. Erection and initial operation of the Mod-5 in Hawaii should take place in 1986. Each successive generation of technology increased reliability and energy capture while reducing the cost of electricity. These advances are being made by gaining a better understanding of the system-design drivers, improving the analytical design tools, verifying design methods with operating field data, and incorporating new technology and innovative designs. Information is given on the results from the first- and second-generation machines (Mod-OA, - 1, and -2), the status of the Department of Interior, and the status of the third-generation wind turbine (Mod-5).

Baldwin, D. H.↗

NASA CARA Prelaunch Analysis and Process

NASA implemented an official Procedural Requirement (NPR) 8079.1 in June 2023, establishing the minimum collision avoidance requirements and associated operational protocols for NASA space flight programs, projects, and spacecraft to protect the space environment by reducing the risk of collision to an acceptable level. Part of the requirement employs a two-fold approach to analyze the satellite design process with conjunction assessment and risk mitigation in mind, during the pre-launch process, led by the Conjunction Assessment Risk Analysis (CARA) Program for non-Human Space Flight (HSF) Missions. This presentation outlines CARA coordination with missions, informed by the NPR, that spans early mission development to operations. CARA is an Agency-level resource that provides support to all NASA non-HSF missions. CARA protects the orbital environment from collision between NASA non-HSF missions and other tracked on-orbit objects. During the pre-formulation and formulation phases, NASA missions undergo a series of conjunction assessment analyses captured in the Orbital Collision Avoidance Plan (OCAP) prior to transitioning to the implementation phase (typically at the Preliminary Design Review (PDR) or equivalent). The OCAP analyses consist of a thorough review of the spacecraft(s) orbit selection and placement, deployment, cataloguing performance, trackability, ephemeris generation, conjunction mitigation options, autonomous maneuvering, and risk assessment parameters which are performed by a dedicated CARA Analysis Team. The results of these analyses, CARA’s formal recommendations, and the mission’s methods for implementing them, are documented in the OCAP. The intent of engaging in this process so early in the mission design phase, is to ensure that conjunction assessment is considered from the outset, thus mitigating costly design changes and operational risks down the road. NASA missions are also required to coordinate their operational processes and conjunction mitigation procedures with CARA in a Conjunction Assessment Operations Implementation Agreement (CAOIA). The aim of this process is to document the conjunction assessment screening process, conjunction risk assessment parameters, conjunction mitigation steps, flight dynamics operations concepts and maneuvers, and the communication and coordination process between the mission’s project manager and CARA. The intent of the CAOIA document is for it to be completed iteratively, and as missions update these elements, corresponding changes are made in the CAOIA. With this process in place, the engagement and coordination between the missions and CARA from early in the design process into mission operations, helps to ensure that missions not only have a robust conjunction assessment concept of operations to reduce conjunction risk for space sustainability, but are also able to achieve their science goals and have a successful mission.

conjunction assessment↗

NASA CARA Prelaunch Analysis and Process

NASA implemented an official Procedural Requirement (NPR) 8079.1 in June 2023, establishing the minimum collision avoidance requirements and associated operational protocols for NASA space flight programs, projects, and spacecraft to protect the space environment by reducing the risk of collision to an acceptable level. Part of the requirement employs a two-fold approach to analyze the satellite design process with conjunction assessment and risk mitigation in mind, during the pre-launch process, led by the Conjunction Assessment Risk Analysis (CARA) Program for non-Human Space Flight (HSF) Missions. This presentation outlines CARA coordination with missions, informed by the NPR, that spans early mission development to operations. CARA is an Agency-level resource that provides support to all NASA non-HSF missions. CARA protects the orbital environment from collision between NASA non-HSF missions and other tracked on-orbit objects. During the pre-formulation and formulation phases, NASA missions undergo a series of conjunction assessment analyses captured in the Orbital Collision Avoidance Plan (OCAP) prior to transitioning to the implementation phase (typically at the Preliminary Design Review (PDR) or equivalent). The OCAP analyses consist of a thorough review of the spacecraft(s) orbit selection and placement, deployment, cataloguing performance, trackability, ephemeris generation, conjunction mitigation options, autonomous maneuvering, and risk assessment parameters which are performed by a dedicated CARA Analysis Team. The results of these analyses, CARA’s formal recommendations, and the mission’s methods for implementing them, are documented in the OCAP. The intent of engaging in this process so early in the mission design phase, is to ensure that conjunction assessment is considered from the outset, thus mitigating costly design changes and operational risks down the road. NASA missions are also required to coordinate their operational processes and conjunction mitigation procedures with CARA in a Conjunction Assessment Operations Implementation Agreement (CAOIA). The aim of this process is to document the conjunction assessment screening process, conjunction risk assessment parameters, conjunction mitigation steps, flight dynamics operations concepts and maneuvers, and the communication and coordination process between the mission’s project manager and CARA. The intent of the CAOIA document is for it to be completed iteratively, and as missions update these elements, corresponding changes are made in the CAOIA. With this process in place, the engagement and coordination between the missions and CARA from early in the design process into mission operations, helps to ensure that missions not only have a robust conjunction assessment concept of operations to reduce conjunction risk for space sustainability, but are also able to achieve their science goals and have a successful mission.

conjunction assessment↗

Vertically stacked photovoltaic and thermal solar cell

According to some embodiments, the present invention provides a novel photovoltaic solar cell system from photovoltaic modules that are vertically arrayed in a stack format using thin film semiconductors selected from among organic and inorganic thin film semiconductors. The stack cells may be cells that are produced in a planar manner, then vertically oriented in an angular form, also termed herein tilted, to maximize the light capturing aspects. The use of a stack configuration system as described herein allows for the use of a variety of electrode materials, such as transparent materials or semitransparent metals. Light concentration can be achieved by using fresnel lens, parabolic mirrors or derivatives of such structures. The light capturing can be controlled by being reflected back and forth in the photovoltaic system until significant quantities of the resonant light is absorbed. Light that passes to the very end and can be reflected back through the device by beveling or capping the end of the device with a different refractive index material, or alternatively using a reflective surface. The contacting between stacked cells can be done in series or parallel. According to some embodiments, the present invention uses a concentrator architecture where the light is channeled into the cells that contain thermal fluid channels (using a transparent fluid such as water) to absorb and hence reduce the thermal energy generation.

14 SOLAR ENERGY↗

Modeling Cost of Offshore Carbon Storage in Saline Reservoirs

Poster presentation to the AAPG-SEG-SPE CCUS 2024 Conference. Offshore saline reservoirs provide a significant and accessible resource for geologic carbon storage (CS). The offshore environment requires distinct approaches to site selection, operations, monitoring, and risk that affect the technoeconomic assessment of offshore CS projects. The National Energy Technology Laboratory (NETL) has developed a CS cost model for offshore saline reservoirs known as CO2_S_COM_Offshore. Based on NETL’s widely used CO2_S_COM cost model for onshore saline CS, CO2_S_COM_Offshore enables technoeconomic analysis of CS in offshore areas. This model comprehensively incorporates multiple facets of offshore CS projects, from regional evaluation and site selection to permitting, transport, operations, monitoring, site closure, and decommissioning. Developed to model cost for offshore United States (US) Exclusive Economic Zones, aspects of this model can be adapted to international projects. Presented at the SPE/AAPG/SEG Carbon Capture Utilization and Storage Conference in Houston, TX, March 11-13, 2024.

Mark-Moser, Mackenzie K.↗

Exploring the Clouds of Venus: Science Driven Aerobot Missions to Our Sister Planet

Venus is essential to our understanding of the evolution and habitability of Earth-size planets throughout the galaxy. The selection of the VERITAS, EnVision, and DAVINCI missions by NASA and ESA in June 2021 is an important step in advancing the science. However, addressing many of the most challenging questions will require in situ platforms that can operate in the Venus environment for extended periods in order to capture the full complexity of our sister planet. Aerobots are aerial vehicles that exploit buoyancy to achieve long-duration operation in the Venus cloud layer where environmental conditions are comparatively benign. Buoyancy control, explained in more detail in a companion paper at this conference, allows aerobots to change altitude with little energy expenditure enabling new scientific measurement opportunities. These include atmospheric chemistry, dynamics, geophysical measurements of the crust and interior and geological investigations enabled by high resolution surface imaging. One aspect to our approach to defining missions that fit within the resource constraints of competitive missions is keeping the scale small. Today’s science-driven appetite for sophisticated measurements and large volumes of data is driving size upwards but advances in technology can enable aerobots that can be delivered to Venus at manageable costs. The other aspect is supporting the aerobot at Venus with orbiters providing data relay, localization and synergistic science. The recently selected orbiters, equipped with low-cost proximity relay systems routinely used at Mars may obviate the need for dedicated orbiters thereby enabling Discovery mission candidates. Four aerobot mission concepts have been defined which fit comfortably within the current New Frontiers (NF) cost cap ($900M in $FY22). One of these concepts would also be a candidate for a Discovery mission if that cost cap ($500M in $FY19) were raised. Raising the NF cost cap would enable more capable aerobot missions combining both altitude control with synergistic orbital observations. Investigations of surface geology at high resolution with subcloud NIR nightside imaging and dropsondes on the dayside of Venus could also benefit from collaborations with foreign contributions.

"O'Rourke, Joseph"↗

Application of machine learning to estimate fireball characteristics and their uncertainty from infrared spectral data

Experiments or events involving high explosives (HE) can be monitored remotely by infrared (IR) sensors to gather information about the configuration or materials involved in the device. Researchers at the Air Force Institute of Technology (AFIT) developed a phenomenological model for HE fireball spectra in the IR range that allows for parameters to be extracted from Fourier transform infrared (FTIR) data. This model includes parameters tied to physical characteristics of the fireball: temperature, size, soot, and gas concentrations. Previous works have sought to recover these parameters by the fitting of either whole spectra or select wavenumber bands to this phenomenological model. Difficulties arise due to the complex relationships between the parameters to be fit. Uncertainty quantification of the estimated fireball parameters is also problematic since HE experiments do not have any ground truth information on the parameters. It is suggested that artificial neural network (ANN) based approaches may be well suited to this problem, because of their ability to capture complex and highly nonlinear relationships. As such, this work seeks to explore the efficacy of deep artificial neural networks (DNNs) for this problem of parameter recovery from spectra and to also investigate the uncertainty of recovering the fireball parameters from FTIR data. Networks are designed using the hyperparameter optimization tool Hyperopt and trained/tested on artificial data generated using the phenomenological model developed by AFIT. The results of applying the network to the artificial data set are compared to a physics-based band approach that uses a selected number of bands based on their physical properties. Information on the uncertainty of estimating parameters from remotely sensed experimental data is obtained by treating the accuracy of the DNN model on artificial data as an upper bound and by examining the impact of emissivity due to soot on parameter estimation error; the results for artificial data are likely to be optimistic as compared to recovering parameters from experimental data.

42 ENGINEERING↗

Recommendations on the Use of Commercial-Off-The-Shelf (COTS) Electrical, Electronic, and Electromechanical (EEE) Parts for NASA Missions - Phase II

This assessment had two Phases. Phase I captured NASA Centers’ current practices for commercial-off-the-shelf (COTS) Electrical, Electronic, and Electromechanical (EEE) parts 1 used in spaceflight systems and ground support equipment (available at https://ntrs.nasa.gov/citations/20205011579) [ref. 1]. The Phase II report provides guidance for selecting and using COTS parts in NASA missions. The approaches proposed in this report differ from current agency practices. This top-level executive summary touches on these new approaches for using COTS parts but does not provide the detailed information that is critical in understanding the rationale behind these new approaches. Readers will need to read the entire report to gain full understanding and effectively use the recommendations herein. NASA’s historical approach to selecting and applying parts has been to define certain parts, primarily specific classes of military specification (MIL-SPEC) parts, as “standard”, leaving all others, including COTS parts, as nonstandard. Standard parts typically are used without further testing (“use-as-is”). Nonstandard parts are subjected to initial screening and subsequent lot acceptance testing of representative samples from each procured lot per MIL-SPEC or similar requirements. Decades later, top-tier commercial part manufacturers have evolved significant manufacturing, statistical control, and technological improvements that can now provide parts as reliable or more reliable than MIL-SPEC parts, when used within their datasheet limits. Concurrently, the space science and exploration community’s needs demand technological advances unavailable with MIL-SPEC parts. This ongoing change necessitates using COTS parts for space missions. Properly selected COTS parts in appropriate applications can offer performance and supply availability advantages compared to MIL-SPEC parts. Their utility and demonstrated reliability result from large volumes and automated production and testing processes. However, careful review and a thorough understanding of their specifications (i.e., datasheet limitations) is needed, and verifying that manufacturer specifications and reliability meet space hardware application needs are necessary. This report recommends MIL-SPEC screening and non-radiation-related lot acceptance testing be reduced or eliminated in cases where evidence of sufficient quality and reliability exists for COTS parts. The extent of NASA's insight into COTS manufacturers and the amount and nature of the needed evidence will differ by mission and will likely be driven by a mission's resources and associated risk posture. To facilitate this goal, two new terminologies have been defined and described: “Industry Leading Parts Manufacturer (ILPM)” and “Established COTS parts.” An ILPM is a COTS manufacturer that produces high quality and reliable parts. Some parts produced by ILPMs, defined as Established COTS parts, do not need any additional MIL-SPEC or NASA screening and lot acceptance testing to be used in space applications. This report provides guidance for selecting, procuring, and applying COTS parts and for performing part-, board-, and system-level COTS parts verification. The recommendation to select Established COTS parts from ILPMs will assure those COTS parts will have comparable quality to corresponding MIL-SPEC parts. Selecting, applying, and verifying Established COTS parts from ILPMs requires a holistic team approach, engaging parts engineers, circuit designers, quality, reliability, and systems engineers, procurement specialists, radiation specialists, avionics leads, and program/project managers. A mission-specific approach tailored to a project’s Mission, Environment, Applications and Lifetime (MEAL) [ref. 2] requirements should be developed and approved by program/project managers. Any associated risks should be clearly identified, quantified, mitigated, and/or accepted. Different approaches are recommended according to program/project Risk Classes A, B, C, and D [ref. 3] and human-rated missions [ref. 4]: 1. Recommend Classes A and B and human-rated missions consider a “MIL-SPEC parts- based design” approach. ”MIL-SPEC parts-based design” approach is one in which most parts are MIL-SPEC parts and Established COTS parts from ILPMs are used only when an equivalent MIL-SPEC part does not meet functional or size, weight, and power (SWaP) or performance requirements, or is not available. 2. Recommend Classes D and Sub-D missions consider a “System of COTS” approach. “System of COTS” approach is one which most parts are Established COTS parts from ILPMs. 3. Recommend Class C missions determine which approach is the best for their projects; that is, use either a “MIL-SPEC parts-based design” approach, “System of COTS” approach, or a combined approach utilizing elements of both. This report intends to provide guidance in using COTS parts for NASA missions with risk classifications of A through D and human-rated missions; but it does not address the costs of using COTS parts. Costs of using COTS parts in different NASA mission classes can vary significantly even if the same parts are used in different risk postures, due to differing verification levels needed. The guidance does not distinguish between critical or non-critical systems, and a given project will need to apply the appropriate guidance based on their risk posture. The intended audience of this report are NASA personnel and commercial practitioners who support NASA’s spaceflight missions, including spaceflight program or project managers, parts engineers, parts manufacturers, radiation engineers, avionics engineers, system engineers, circuit design engineers, reliability engineers, safety and mission assurance (SMA) personnel, and parts procurement specialists. The NEPP Program will perform a pathfinder study to explore implementing the guidance in this NESC report. An ILPM verification process is not the same as conventional vendor qualification processes performed according to military standards and specifications. This NESC report intends to provide guidance in utilizing available parts data from ILPM manufacturers for parts assurance assessments needed for NASA missions. The report also captured the current practices from DoD and Federal Aviation Administration (FAA) in Section 10. Note each DoD and FAA report was provided by the corresponding agencies regarding their practices, which are independent from the NESC recommendations in the report.

Commercial-Off-The-Shelf↗

Integrating the PanDA Workload Management System with the Vera C. Rubin Observatory

The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of petabytes of raw image data and associated calibration data over the course of the experiment’s run. More than 20 terabytes of data must be stored every night, and annual campaigns to reprocess the entire dataset since the beginning of the survey will be conducted over ten years. The Production and Distributed Analysis (PanDA) system was evaluated by the Rubin Observatory Data Management team and selected to serve the Observatory’s needs due to its demonstrated scalability and flexibility over the years, for its Directed Acyclic Graph (DAG) support, its support for multi-site processing, and its highly scalable complex workflows via the intelligent Data Delivery Service (iDDS). PanDA is also being evaluated for prompt processing where data must be processed within 60 seconds after image capture. This paper will briefly describe the Rubin Data Management system and its Data Facilities (DFs). Finally, it will describe in depth the work performed in order to integrate the PanDA system with the Rubin Observatory to be able to run the Rubin Science Pipelines using PanDA.

79 ASTRONOMY AND ASTROPHYSICS↗

Enhanced Carbon Capture Behavior of Carbon Fibers via Ionic Liquid Modification

Carbon-based materials are widely deployed in carbon capture but are only limited to physisorption procedures. Further extending functionalized carbon materials to CO 2 chemisorption under low CO 2 concentration is highly desirable yet challenging. In this study, a carbon fiber composed of solely ultra-micropores (~0.45 nm) was deployed as the precursor to avoid the pore blocking effect, which was modified by superbase-derived ionic liquids (ILs) containing strong interaction sites with CO 2 . By forming a thin coating layer on the surface, the as-afforded surface-functionalized fiber materials demonstrated enhanced CO 2 uptake capacity and improved CO 2 sorption kinetics, as evaluated by both the volumetric method and thermogravimetric analysis, as well as the calculated energy distribution curves. The achievements made in this work provide guidance on the functionalization of carbon-based materials towards enhanced CO 2 chemisorption by forming a thin layer of selected IL coating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A phased workflow to define permit‐ready locations for large volume CO 2 injection and storage

Abstract To‐date, only two UIC Class VI permits have been issued by the US Environmental Protection Agency. We illustrate a four‐phase workflow to first identify regional storage resources and then down‐select sites to yield permit‐ready locations that can accept and store large volumes of CO 2 . Specific permit requirements should guide objectives and define deliverables of respective workflow phases. In the first phase we used available regional data and screened structure and injection zones to locate resources that match CO 2 volumes planned to be captured. Available data were also used to assess presence and depth of usable groundwater, the key resource being protected via permitting. We then used advanced, closed‐form, analytical solutions (EASiTool) to estimate CO 2 injectivity into each hydrologically connected injection compartment. In the second phase we acquired and conditioned additional wireline logs and leased available seismic datasets. We interpreted the depositional systems from wireline well‐log character and mapped sandbody geometry to interpolate injection and confining‐zone distribution. Using available data, we mapped faults and locations of freshwater and overpressure (or other capacity‐limiting geologic parameters) in more detail. In the third phase, we used the augmented geologic data to develop a static model for the selected area, extracted the areas of highest interest, and generated and ran dynamic (flow) models. In a fourth phase, we reduced major uncertainties identified in earlier phases. Our case study indicates that to complete preparation of a permit application requires (1) improved lithologic characterization information (thicknesses and horizontal and vertical connectivity) and (2) better definition of poorly defined local faults. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

58 GEOSCIENCES↗

A review of artificial intelligence applications in manufacturing operations

Abstract Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these challenges, AI has the potential to be extremely helpful in manufacturing, particularly in applications such as predictive maintenance, quality assurance, and process optimization. It is important to consider the specific needs and capabilities of each manufacturing scenario when deciding whether and how to use AI in manufacturing. This review identifies current developments, challenges, and future directions in AI/ML relevant to manufacturing, with the goal of improving understanding of AI/ML technologies available for solving manufacturing problems, providing decision‐support for prioritizing and selecting appropriate AI/ML technologies, and identifying areas where further research can yield transformational returns for the industry. Early experience suggests that AI/ML can have significant cost and efficiency benefits in manufacturing, especially when combined with the ability to capture enormous amounts of data from manufacturing systems.

Plathottam, Siby Jose↗

Field-scale dynamics of planting dates in the US Corn Belt from 2000 to 2020

Crop planting dates are a dynamic feature of agricultural systems that respond to short- and long-term climate signals, crop and cultivar selection, and technology changes. Planting date records are essential for yield gap analyses, accurate crop modeling, and tracking farmer adaptations to weather and climate change. Although planting dates have high variation at local scales due to heterogeneity in farm resources and decision-making, available long-term data on planting dates is largely restricted to aggregated regional statistics or, at best, satellite-derived datasets with limited spatiotemporal extent and at resolutions unable to distinguish individual fields (> 250 m). Here, we generated retrospective annual field-scale (30 m) planting date maps for both maize and soybeans spanning 2000-2020 across a 12 state region in the United States Corn Belt based on Landsat satellite data and a large ground sample of over 28,000 maize and soybean fields. Using training data from 2015-2020 for model selection, we found that planting date predictions improved with harmonic regression of Landsat data and additional annual weather covariates. The preferred random forests model approximately doubled performance compared to a null model based on state median planting dates, capturing 47% of field-level variation for maize (mean absolute error, MAE = 7.4 days) and 44% for soybeans (MAE = 7.5 days) against held-out ground truth test data for 2008-2014. We also evaluated the full 2000-2020 dataset with state agricultural statistics, finding strong agreement with median planting dates for maize (R 2 = 0.76, MAE = 4.4 days) and slightly lower agreement for soybeans (R 2 = 0.65, MAE = 5.4 days) when aggregated to the state level. We then used this new dataset to analyze environmental determinants of planting dates at a finer-scale than previously possible, controlling for unobserved variation at the sub-state district level. We found that during 2000-2020, each standard deviation increase in rainfall delayed planting by ~ 2.5 days, and fields with higher soil productivity ratings tended to be planted earlier. We did not find meaningful trends over the last two decades in planting dates for maize or soybeans, in contrast to trends towards earlier planting dates late last century and predicted for this period in climate adaptation studies. We hypothesize increases in early season rainfall may have inhibited these shifts towards earlier planting. Remotely sensed planting dates will be a useful tool for yield gap analyses, crop simulation modeling, and ongoing assessment of climate adaptation.

54 ENVIRONMENTAL SCIENCES↗

Alkali-induced catalytic tuning at metal and metal oxide interfaces

Alkali metals have been recognized as effective promoters in heterogeneous catalysis, capable of enhancing catalytic activity and tuning product distributions. Over the past few decades, significant efforts have been made aiming to reveal the mechanisms underlying the promoting effect of alkalis. However, the roles that alkali metals play in the catalytic process remain elusive due to challenges in capturing their catalytic behaviours upon exposure to reactive environments. This review summarizes recent surface science and theoretical studies of alkali (potassium, cesium)-decorated metal and metal oxide model catalysts, revealing the crucial tuning by alkalis of activity and selectivity for CO 2 hydrogenation. The analysis of electronic structures identifies the selective binding mechanism of the positively charged alkali ions on the surface, being able to reduce the surface work function and lead to strong electron polarization on the surfaces. Depending on the alkali–support interaction, the deposition of alkalis can selectively modify the bindings of reaction intermediates involved in CO 2 hydrogenation via the interplay among the ionic, covalent and electrostatic tunings. As a result, CO 2 can be effectively activated and converted into diverse products at the alkali–support interface, ranging from formic acid to methanol and ethanol. The identified selective bond-tuning advances the application of alkalis in promoting catalytic activity and controlling catalytic selectivity at alkali–support interfaces.

03 NATURAL GAS↗

Determination of latent dimensionality in international trade flow

Currently, high-dimensional data is ubiquitous in data science, which necessitates the development of techniques to decompose and interpret such multidimensional (aka tensor) datasets. Finding a low dimensional representation of the data, that is, its inherent structure, is one of the approaches that can serve to understand the dynamics of low dimensional latent features hidden in the data. Moreover, decomposition methods with non-negative constraints are shown to extract more insightful factors. Nonnegative RESCAL is one such technique, particularly well suited to analyze self-relational data, such as dynamic networks found in international trade flows. Particularly, non-negative RESCAL computes a low dimensional tensor representation by finding the latent space containing multiple modalities. Furthermore, estimating the dimensionality of this latent space is crucial for extracting meaningful latent features. Here, to determine the dimensionality of the latent space with non-negative RESCAL, we propose a latent dimension determination method which is based on clustering of the solutions of multiple realizations of non-negative RESCAL decompositions. We demonstrate the performance of our model selection method on synthetic data. We then apply our method to decompose a network of international trade flows data from International Monetary Fund and shows that with a correct latent dimension determination, the resulting features are able to capture relevant empirical facts from economic literature.

97 MATHEMATICS AND COMPUTING↗