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NASA NTRSDate not supplied

Space Crop Production Gaps and Challenges

As astronauts venture farther from Earth, and stay for longer periods, the space food system will increase in importance. Crop production can supplement a pre-packaged space diet to provide nutrition and dietary variety for space crews. In future missions, bioregenerative approaches may be used to generate a larger percentage of the diet, as well as help to reduce life support system burdens and resupply from Earth. Plants may also provide behavioral health benefits to crew members living in the isolated, confined environment of a space habitat. A number of unique challenges exist for growth of plants in microgravity and on other reduced gravity surfaces like the moon and Mars. Testing plant growth inside the Veggie and Advanced Plant Habitat (APH) chambers on the International Space Station is allowing us to understand the impacts of gravity and spaceflight on crop growth, nutritional content, acceptability, and the importance of plants to astronauts living and working away from Earth. We are also gaining a better understanding of food safety concerns and the behavior of space plant microbiomes and plant pathogens, but major gaps in knowledge remain. As we move from research towards operational space crop production to enable exploration, there are numerous gaps in technology, knowledge, and practice related to space crop growth that must be addressed. Research and development in key focus areas such as effective water and nutrient delivery at variable gravity levels, autonomous plant health monitoring, growth system cleaning and disinfection, and selection of ideal space crops are needed to fill these gaps. Breeding or engineering custom space crops may impact areas including plant growth and development, plant physiology, produce nutrition, organoleptic acceptability, and post-harvest characteristics, and these may further enable space crop production scenarios. Space crop challenges are multifaceted and require diverse interdisciplinary teams working together to develop effective solutions. Solving these requires an array of skill sets from across the biological and physical sciences, engineering, and human social sciences. Solutions to help ensure food security off-Earth may also translate to more sustainable terrestrial crop production approaches, and regular dialog between industry, academia, and government organizations working in related fields benefit all. Additional help can come from engagement with student researchers at various levels through courses, participatory science projects, and open science activities which can provide useful data. Global coordination and integration between space agencies and partners will be essential.

Gioia Massa↗
DOE OSTI2023

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↗
DOE OSTI2025

Sensor Placement Optimization Study for the Built Environment: Next Steps Report

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear incidents. First responder organizations that implement systems of fixed-position sensors face numerous decisions regarding sensor selection, quantity, and placement. Researchers at Pacific Northwest National Laboratory (PNNL) have evaluated the performance of several hypothetical sensor systems during a simulated activation of a radiological dispersal device. Due to technical limitations, PNNL’s analysis was limited to a single location and number of scenarios. This document describes additional research and analysis that would result in improved guidance to first responder organizations considering installation of radiation monitoring systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1988

Deccan volcanism at the Cretaceous-Tertiary boundary

The accuracy with which one can claim that Deccan trap volcanism occurred at the Cretaceous-Tertiary boundary (KTB) over a very short time interval is of key importance in deciding whether a volcanic origin of the KTB events should be taken seriously. In the two years since paleomagnetic, paleontological and geodynamic evidence was published, further data have become available and the case now appears to be well constrained. The Ar-40/Ar-39 results from six labs have yielded some 24 reliable plateau ages that narrow the age range to 65 to 69 Ma. Moreover, it appears that a significant part of this range results from inter-lab spread and possible minor alteration. Paleontology demonstrates that volcanism started in the Maestrichtian, more precisely in the A. mayaroensis zone. Paleomagnetism shows that volcanism spanned only 3 chrons and only one correlation remains possible, that of the main central reversed chron with 29R. Therefore, whereas Ar-40/Ar-39 is able only to restrict the duration of volcanism to some 4 Ma, paleomagnetism restricts it to 0.5 Ma. Using some geochemical indicators such as C-13 as proxy, it is suggested that volcanism actually consists of a few shorter events of unequal magnitude. Extrusion rates may be as high as 100 cu km/yr and fissure lengths as long as several 100 km. Such a scenario appears to be at least as successful as others in accounting for most anomalies observed at the KTB. Particularly important are Iridium and other platinum group elements (PGE) profiles, Sr-87/Sr-86, C-13, 0-18, other exotic geochemical signatures, spherules, soot, shocked minerals, selective and stepwise extinctions. The environmental impact of CO2 possibly released during explosive phases of volcanism, and SO2 released during effusive phases, and the ability of volcanism to ensure worldwide distribution of KTB products are now all addressed. In conclusion, the case for a causal link between internal hotspot activity, birth of the Reunion hotspot itself as the Deccan and KTB events appears to rest on an increasingly stronger basis.

Courtillot, V.↗
NASA NTRS1993

A comparison of nuclear thermal rocket development cost and schedule for piloted missions to Mars

In Fiscal Year 1992, NASA led a team, including DOE, universities, and industry, that evaluated various schedule and cost scenarios for development of nuclear thermal rocket propulsion systems for piloted Mars exploration. This paper summarizes the results of two of these studies: (1) a so-called 'Fast Track' approach, that would result in technology readiness level 6 (TRL-6-system ground testing complete) by the year 2000, and (2) a slower program that results in TRL-6 by 2006. Both scenarios included a concurrent engineering approach. Costs and schedules for the two scenarios are compared. In addition to the six-year schedule delay, the TRL-6 in 2006 scenario is estimated to increase the cost of the program from $4.7 billion to $5.8 billion (in real-year dollars). On the positive side, the technical program should be better, since nuclear testing of fuel elements may be possible prior to concept down-select, resulting in a more informed decision.

Clark, John S.↗
NASA NTRS2009

Heart Rhythm Monitoring in the Constellation Lunar and Launch/Landing EVA Suit: Recommendations from an Expert Panel

There are currently several physiological monitoring requirements for EVA in the Human-Systems Interface Requirements (HSIR) document. There are questions as to whether the capability to monitor heart rhythm in the lunar surface space suit is a necessary capability for lunar surface operations. Similarly, there are questions as to whether the capability to monitor heart rhythm during a cabin depressurization scenario in the launch/landing space suit is necessary. This presentation seeks to inform space medicine personnel of recommendations made by an expert panel of cardiovascular medicine specialists regarding in-suit ECG heart rhythm monitoring requirements during lunar surface operations. After a review of demographic information and clinical cases and panel discussion, the panel recommended that ECG monitoring capability as a clinical tool was not essential in the lunar space suit; ECG monitoring was not essential in the launch/landing space suit for contingency scenarios; the current hear rate monitoring capability requirement for both launch/landing and lunar space suits should be maintained; lunar vehicles should be required to have ECG monitoring capability with a minimum of 5-lead ECG for IVA medical assessments; and, exercise stress testing for astronaut selection and retention should be changed from the current 85% maximum heart rate limit to maximal, exhaustive 'symptom-limited' testing to maximize diagnostic utility as a screening tool for evaluating the functional capacity of astronauts and their cardiovascular health.

Scheuring, Richard A.↗
NASA NTRS2015

Avionics Configuration Assessment for Flightdeck Interval Management: A Comparison of Avionics and Notification Methods

Flightdeck Interval Management is one of the NextGen operational concepts that FAA is sponsoring to realize requisite National Airspace System (NAS) efficiencies. Interval Management will reduce variability in temporal deviations at a position, and thereby reduce buffers typically applied by controllers - resulting in higher arrival rates, and more efficient operations. Ground software generates a strategic schedule of aircraft pairs. Air Traffic Control (ATC) provides an IM clearance with the IM spacing objective (i.e., the TTF, and at which point to achieve the appropriate spacing from this aircraft) to the IM aircraft. Pilots must dial FIM speeds into the speed window on the Mode Control Panel in a timely manner, and attend to deviations between actual speed and the instantaneous FIM profile speed. Here, the crew is assumed to be operating the aircraft with autothrottles on, with autopilot engaged, and the autoflight system in Vertical Navigation (VNAV) and Lateral Navigation (LNAV); and is responsible for safely flying the aircraft while maintaining situation awareness of their ability to follow FIM speed commands and to achieve the FIM spacing goal. The objective of this study is to examine whether three Notification Methods and four Avionics Conditions affect pilots' performance, ratings on constructs associated with performance (workload, situation awareness), or opinions on acceptability. Three Notification Methods (alternate visual and aural alerts that notified pilots to the onset of a speed target, conformance deviation from the required speed profile, and reminded them if they failed to enter the speed within 10 seconds) were examined. These Notification Methods were: VVV (visuals for all three events), VAV (visuals for all three events, plus an aural for speed conformance deviations), and AAA (visual indications and the same aural to indicate all three of these events). Avionics Conditions were defined by the instrumentation (and location) used to present IM information to crews: (1) Integrated (IM information is embedded in extant PFD (Primary Flight Display), ND (Navigation Display), EICAS (Engine Indicating and Crew Alerting System) displays); (2) EFB_Aft (IM information is only supplied in an EFB and mounted in location similar to that for MITRE's UPS work); (3) EFB_Fore (IM information is only supplied in an EFB which is mounted more forward, under the side window), and (4) EFB_Aft plus use of an AGD (the same IM information is supplied in an EFB and on an AGD, both mounted in locations similar to that in MITRE's UPS work ). Twelve commercial pilot crews flew descent scenarios (VNAV Speed with the mode control panel (MCP) speed window open until flaps extended, then VNAV Path) in a commercial transport flight simulator with realistic visual scene and communications. The results of this study serve three practical aims: (1) contribute to the down-select of avionics configuration for future assessment of the ASTAR spacing algorithm at NASA; (2) provide information useful to the FAA Human Factors Division (ANG-C1)'s mission to identify issues pertinent to flight certification of, and flight standards; (3) identify methodological considerations in support of future FIM human-in-the-loop (HITL) investigations.

Latorella, Kara A.↗
DOE OSTI2024

Advancements in Multiphysics Microdepletion Analysis of an eVinci TM -like Microreactor Leveraging OpenMC-CRAB Workflow

Nuclear microreactors (MRs) are a class of nuclear reactor technology, characterized by reduced dimensions, modular design, and reduced power output in contrast to conventional Light Water Reactors (LWRs). MRs are proposed for supplying electricity and eventual process heat to remote locations, such as military installations and disaster-affected areas. Current research work sponsored by the US Department of Energy Microreactor Program (MRP) is devoted to the development of novel modeling and simulation tools to better support MR vendors and regulatory bodies. Notably, the NRC is projected to utilize the CRAB multiphysics software driver for executing both design and beyond-design-basis accident analyses. Furthermore, the NRC has been utilizing the MELCOR code to calculate mechanistic source terms during accidents. Since MELCOR relies on isotopic inventory and reactor temperature/power profiles under accident conditions, which theoretically can be derived from CRAB, the goal is to establish a comprehensive CRAB-MELCOR computational framework. Past work was focused on testing and demonstrating CRAB's capability to generate results that can be used to inform mechanistic source term calculations in MELCOR. In particular, a computational workflow leveraging OpenMC-generated microscopic cross sections and CRAB was first applied to perform multiphysics microscopic depletion calculation followed by an accident scenario for a stylized microreactor problem. In fiscal year 2024, the research work has been focused on applying the OpenMC-CRAB workflow, which was first tested in fiscal year 2023, to a realistic 3D heat-pipe cooled MR problem representative of the eVinci TM design. The latter computational problem was developed with inputs from WEC to conserve selected neutronic and thermal characteristics of the eVinci TM design without releasing proprietary data. The results of this simulation, encompassing isotopic inventory, power density distribution, and kinetic parameters, will inform both MELCOR and the WEC-developed FATE code for mechanistic source terms calculations. The results from the two codes will then be compared for code verification purposes. This report contains the design characteristics of the realist heat pipe cooled microreactor developed as a use-case for the verification exercise, and the current results for the multiphysics microscopic depletion performed with the OpenMC-CRAB workflow. The results include eigenvalue as a function of time, power distribution at EOL, in addition to nuclides inventory's time evolution and spatial distribution. Finally, we report improvements to the workflow efficiency achieved through a collaboration with the NEAMS programs. Through this collaborative effort, we were able to strongly decrease the computational time for the multiphysics microdepletion calculation (i.e., from 17.4 hours to 5.7 hours on 280 processors) in addition to simplifying the interface to generate isotopics spatial distribution utilizable by FATE and MELCOR. Future work, including the improvement of the current microscopic cross-sections' library and the simulation of an accident scenario at EOL, is also discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Sensor Placement Optimization Study for the Built Environment: Operational Use Cases

Systems of fixed-position radiation sensors can provide information that assists emergency responders following nuclear and radiological incidents. State, local, tribal, and territorial (SLTT) government agencies that implement systems of fixed-position sensors are faced with numerous decisions regarding sensor selection, quantity, and placement. To develop guidance on implementation of radiation detection systems, we simulated the release of radioactive material in an urban environment using a combination of three models: the Weather Research Forecasting (WRF), Quick Urban and Industrial Complex (QUIC), and Monte Carlo N-Particle (MCNP) models. We then evaluated the performance of several hypothetical sensor systems. The small number of simulations we conducted are not sufficient to generate definitive design guidance for radiation sensor systems, but we did identify trends that would be of interest to emergency planners. For a scenario that releases 1000 curies of Cs-137, radiation detectors were needed at 500-meter intervals to have a high likelihood of event detection and to estimate source location and plume detection. We also noted that optimal detector altitude varied with distance to the source. We recommend additional research in this area be conducted to support developing sensor placement guidelines that expand on a range of locations, isotopes, activity levels, and different weather conditions. Original simulation strategies included a range of environments, additional radioisotopes (Am241 and AmBe), and a larger selection of sensor types. These types of expansions would support SLTT guidance on sensor system recommendations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Recovered supernova Ia rate from simulated LSST images

Aims.TheVera C. RubinObservatory’s Legacy Survey of Space and Time (LSST) will revolutionize time-domain astronomy by detecting millions of different transients. In particular, it is expected to increase the number of known type Ia supernovae (SN Ia) by a factor of 100 compared to existing samples up to redshift ∼1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of the properties and rates of these objects. However, the impact of all other sources of uncertainty on the measurement of the SN Ia rate must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SN Ia rate can put constraints on the evolutionary scenarios of different SN Ia progenitors. Methods.We used simulated data from the Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) and LSST Data Preview 0 to measure the SN Ia rate on a 15 deg 2 region of the “wide-fast-deep” area. We selected a sample of SN candidates detected in difference images, associated them to the host galaxy with a specially developed algorithm, and retrieved their photometric redshifts. We then tested different light-curve classification methods, with and without redshift priors (albeit ignoring contamination from other transients, as DC2 contains only SN Ia). We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate. Results.We measured the SN Ia rate, analyzing the impact of uncertainties due to photometric redshift, host-galaxy association and classification on the distribution in redshift of the starting sample. We find that we are missing 17% of the SN Ia, on average, with respect to the simulated sample. As 10% of the mismatch is due to the uncertainty on the photometric redshift alone (which also affects classification when used as a prior), we conclude that this parameter is the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SN Ia rate, including synergies with other surveys, which may help us to use the rate to discriminate different progenitor models.

Astronomy & Astrophysics↗
DOE OSTI2021

Robust Output Feedback Control Design for Inertia Emulation by Wind Turbine Generators

Wind generation has gained widespread use as a renewable energy source. Most wind turbines and other renewables connected to the grid through converters result in a reduction in the natural inertial response to grid frequency changes. The doubly-fed induction generator (DFIG) can be controlled to compensate for this reduction and, in fact, provide faster response than traditional synchronous machines. This paper proposes to design observer based output feedback linear quadratic regulator (LQR) and H control laws to realize the inertia emulation function and deliver fast frequency support. Furthermore, the aim is to track the reference speed by a diesel synchronous generator (DSG) in order to reach the desired inertia. The control signal is computed based on a reduced order model using the balanced truncation technique. A comparison with selective modal analysis (SMA) and balanced truncation model reduction techniques is presented. Comprehensive results show the effective emulation of synthetic inertia by implementing the control laws on a nonlinear three- phase diesel-wind system. The proposed technique is analyzed for different short circuit ratio (SCR) scenarios.

17 WIND ENERGY↗
DOE OSTI2020

Low-Temperature Plasma Treatment for Enhanced Recovery of Highly Valued Critical REEs from Coal (Final Report)

The principle objective of this project was to develop a novel process flowsheet using low-temperature plasma treatment (LTP) integrated with conventional hydrometallurgical processes to recover rare earth elements (REEs), especially highly valued REEs (i.e. scandium and critical REEs), from coal and coal byproducts. LTP treatment was used to pretreat the solid feed material prior to leaching in an effort to improve the leaching characteristics of the REEs and potentially reduce acid consumption. Initially, a detailed experimental program was performed on a laboratory LTP furnace to identify a set of process parameter values to be used for assessing the enhanced leaching performance achieved on four specific gravity fractions of West Kentucky No. 13 and Fire Clay coarse coal refuse materials. High-temperature oxidation (HTO)) was also evaluated as a means for improving REE leachability on the same fractions of both coal sources. The lixiviants used to assess leachability improvements included: i) untreated water, ii) 0.1 M ammonium sulfate solution and iii) 1.2 M sulfuric acid solution at a temperature of 75°C. The laboratory data was used to develop multiple process flow sheets using HTO only to produce a rare earth oxide mix concentrate or utilizing both LTP and HTO treatment processes to generate a high purity heavy REO mix concentrate and a light REO mix concentrate. A techno-economic analysis was performed on each circuit. Low-temperature plasma oxidation was found to enhance REE leaching characteristics for all specific gravity (SG) fractions of the West Kentucky No. 13 coarse refuse material. The leaching recovery improvement was preferentially achieved for the heavy REEs with higher values obtained when treating the lower density fraction material. For example, the leaching recovery for the heavy REEs in the untreated 1.6 SG Float fraction material was 8% in a 0.1 M ammonium sulfate solution. After LTP treatment for 32 hours, heavy REE recovery increased to 33%. The corresponding recovery value for the light REEs was 10%. These findings indicate a strong affinity of the heavy REEs with the organic material, which is the component being reduced in content during the LTP treatment. Scanning electron micrographs showed the development of a honeycomb structure with increased LTP treatment with higher surface area as confirmed from BET measurements. Higher surface area promotes improved leaching efficiency due to enhance chemical interactions. When using 1.2 M sulfuric acid, the LTP treatment was found to provide a heavy REE recovery increase from 23% to 53% for the 1.6 SG Float fraction which corresponded to an ash content increase from around 20% to 35%. However, LTP treatment provided no improvement in leaching characteristic for the 2.2 SG sink material in the acid solution, which was likely due to the low organic content. The LTP treatment of the Fire Clay SG fractions provided no improvement in REE leaching characteristic, which may be due to the association with REE minerals such as monazite and REE-associated mineral matter such as clays. High temperature oxidation using temperatures in the range of 600-750OC was found to significantly enhance the leaching characteristics of both the light and heavy REEs for all density fractions in both coarse coal refuse materials. Generally, the increase in light REE recovery for the West Kentucky material was from 15% for the untreated material to 90% for the HTO treated material at 600°C. Recovery values dropped significantly when using temperatures below 600°C and above 750°C. The impact of the excessive temperatures was most likely a result of sintering. For the heavy REEs, HTO significantly improved recovery in the lighter SG fractions, which may be due to an affinity with the organic content. Only limited heavy REE recovery improvement was obtained for the denser SG fractions. Another benefit of HTO is the conversion of calcium-based minerals to a very soluble calcium oxide, which is removable using a mild acid solution, and the conversion of Fe minerals to relatively insoluble minerals such as hematite and magnetite. The pregnant leaching solution produced from the leaching of all SG fractions obtained from both coal sources was treated using two stages of solvent extraction procedurally modeling a rougher-cleaner circuit followed by oxalic acid precipitation. Rare earth oxide products having a purity greater than 97% was produced from nearly all of the SG fractions. A novel process flowsheet was developed based on the selective leaching of heavy REEs that was made possible through LTP treatment of West Kentucky No. 13 coarse refuse followed by salt leaching. In the flowsheet, coal refuse material is ground to a top size of 1mm and then treated by LTP. The treated material is mixed into a 0.1 M ammonium sulfate solution and then filtered to produce a heavy REE enriched pregnant leach solution. The heavy REEs are concentrated by two stages of selective precipitation to produce a heavy REE mix oxalate and then roasted to obtain a heavy REO mix concentrate. The solid residues remaining after salt leaching is dried and then subjected to HTO treatment followed by concentration using selective precipitation and roasting to produce a light REO mix concentrate. An alternative circuit was developed using HTO treatment only to treat 100% of the coarse refuse material followed by selective precipitation and roasting to generate a high purity REO mix product. A techno-economic analysis performed for the treatment of West Kentucky No. 13 and Fire Clay coarse refuse based on a hypothetical 500-tph plant revealed that the net present value for all scenarios was significantly negative. Primary reasons include: i) a substantial decrease in the basket value of the final product relative to the feed and ii) high chemical costs relative to the amount of product generated. The basket value reduction was primarily due to little to no scandium recovery due to poor leaching characteristics when using low acid concentrations as necessitated by the low feed grades. Operating costs were primarily influenced by the chemical costs relative to the kilograms of concentrate produced and feed grade. For the Fire Clay coarse refuse material, the total operating cost was estimated to be $354 per kg of REO produced which was higher than the basket value of the REO product ($276/kg). Approximately 37% of the total cost was the sulfuric acid used during the leaching process. A comparative analysis performed to assess the economic viability of using low-temperature plasma furnaces found that market value enhancement for the generation of both heavy REO and light REO concentrates will be needed in addition to significant technology advancements to reduce the cost of plasma furnaces.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Application of Electromagnetic Methods for Reservoir Monitoring with Emphasis on Carbon Capture, Utilization, and Storage

The Controlled-Source ElectroMagnetic (CSEM) method provides crucial information about reservoir fluids and their spatial distribution. Carbon dioxide (CO2) storage, enhanced oil recovery (EOR), geothermal exploration, and lithium exploration are ideal applications for the CSEM method. The versatility of CSEM permits its customization to specific reservoir objectives by selecting the appropriate components of a multi-component system. To effectively tailor the CSEM approach, it is essential to determine whether the primary target reservoir is resistive or conductive. This task is relatively straightforward in CO2 monitoring, where the injected fluid is resistive. However, for scenarios involving brine-saturated (water-wet) or oil-wet (carbon capture, utilization, and storage—CCUS) reservoirs, consideration must also be given to conductive reservoir components. The optimization of data acquisition before the survey involves analyzing target parameters and the sensitivity of multi-component CSEM. This optimization process typically includes on-site noise measurements and 3D anisotropic modeling. Based on our experience, subsequent surveys tend to proceed smoothly, yielding robust measurements that align with scientific objectives. Other critical aspects to be considered are using magnetotelluric (MT) measurements to define the overall background resistivities and integrating real-time quality assurance during data acquisition with 3D modeling. This integration allows the fine tuning of acquisition parameters such as acquisition time and necessary repeats. As a result, data can be examined in real-time to assess subsurface information content while the acquisition is ongoing. Consequently, high-quality data sets are usually obtained for subsequent processing and initial interpretation with minimal user intervention. The implementation of sensitivity analysis during the inversion process plays a pivotal role in ensuring that the acquired data accurately respond to the target reservoirs’ expected depth range. To elucidate these concepts, we present an illustrative example from a CO2 storage site in North Dakota, USA, wherein the long-offset transient electromagnetic method (LOTEM), a variation of the CSEM method, and the MT method were utilized. This example showcases how surface measurements attain appropriately upscaled log-scale sensitivity. Furthermore, the sensitivity of the CSEM and MT methods was examined in other case histories, where the target reservoirs exhibited conductive properties, such as those encountered in enhanced oil recovery (EOR), geothermal, and lithium exploration applications. The same equipment specifications were utilized for CSEM and MT surveys across all case studies.

Barajas-Olalde, César↗
NASA NTRS2023

Machine Learning to Increase the Quality and Repeatability of 3D Printing - Workflow

The imprecise nature of three-dimensional (3D) printing limits the technology’s use beyond prototyping. For production of end-use parts, such as those for aerospace applications, improvements are needed to enhance quality and repeatability. Much of the difficulty in obtaining high quality printed parts lies in finding optimum printing parameters. Currently, this requires trial and error performed by an expert. Finding the optimum printing parameters is also obfuscated by the variation in optimum parameters throughout the part due to part geometry and printer effects. To allow for locally optimized printing parameters, one can envision a machine learning algorithm that could take in an object, predict the best printing parameters, and communicate these parameters to a printer. With this scenario in mind, we developed a tool that can predict and implement locally optimized printing parameters in 3D printing. This tool consists of elements designed to detect errors in a printed part, predict the probability of local flaws occurring at each point in the part, and select the optimal local parameters for the highest quality part given hardware limitations. The results of this work were highlighted in Advanced Materials Technologies. In this paper, we will discuss in greater depth the workflow and algorithms involved with this tool that were not detailed in the journal publication.

additive manufacturing↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs: Preprint

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN) architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS dataset with 37 simulated scenarios, the trained and validated network predicted the production temperature for 6 production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells, at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model and may lead to converting these wells to producers to access under-exploited zones in the reservoir. Data gathering activities are planned for the first quarter of 2021.

40 EE - Geothermal Technologies Office (EE-4G)↗
NASA NTRS2017

Hybrid Guidance Control for a Hypervelocity Small Size Asteroid Interceptor Vehicle

Near-Earth Objects (NEOs) are comets and/or asteroids that have orbits in proximity with Earth's own orbit. NEOs have collided with the Earth in the past, which can be seen at such places as Chicxulub crater, Barringer crater, and Manson crater, and will continue in the future with potentially significant and devastating results. Fortunately such NEO collisions with Earth are infrequent, but can happen at any time. Therefore it is necessary to develop and validate techniques as well as technologies necessary to prevent them. One approach to mitigate future NEO impacts is the concept of high-speed interceptor. This concept is to alter the NEO's trajectory via momentum exchange by using kinetic impactors as well as nuclear penetration devices. The interceptor has to hit a target NEO at relative velocity which imparts a sufficient change in NEO velocity. NASA's Deep Impact mission has demonstrated this scenario by intercepting Comet Temple 1, 5 km in diameter, with an impact relative speed of approximately 10 km/s. This paper focuses on the development of hybrid guidance navigation and control (GNC) algorithms for precision hypervelocity intercept of small sized NEOs. The spacecraft's hypervelocity and the NEO's small size are critical challenges for a successful mission as the NEO will not fill the field of view until a few seconds before intercept. The investigation needs to consider the error sources modeled in the navigation simulation such as spacecraft initial state uncertainties in position and velocity. Furthermore, the paper presents three selected spacecraft guidance algorithms for asteroid intercept and rendezvous missions. The selected algorithms are classical Proportional Navigation (PN) based guidance that use a first order difference to compute the derivatives, Three Plane Proportional Navigation (TPPN), and the Kinematic Impulse (KI). A manipulated Bennu orbit that has been changed to impact Earth will be used as a demonstrative example to compare the three methods. In addition, a hybrid approach that is a combination between proportional navigation and kinematic impulse will be investigated to find an effective, error tolerant, and power saving approach. A 3-dimension mission scenario for both the asteroid and the interceptor spacecraft software simulator is developed for testing of the controllers. The current result demonstrates that a miss distance magnitude of less than 10m is found using the PN and TPPN guidance laws for small asteroid in the presence of error in the spacecraft states. Moreover, the paper presents these results and also the hybrid control approach simulation results.

asteroid↗
NASA NTRS2008

Automated Generation and Assessment of Autonomous Systems Test Cases

This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.

Testing challenges↗
DOE OSTI2021

Efficient prediction of concentrating solar power plant productivity using data clustering

Concentrating solar power (CSP) plants convert solar energy to electricity and can be deployed with a thermal storage capability to shift electricity generation from time periods with available solar resource to those with high electricity demand or electricity price. Rigorous optimization of plant design and operational strategies can improve the market-competitiveness and commercial viability; however, such optimization may require hundreds of annual performance simulations, each of which can be computationally expensive when including considerations such as optimization of dispatch scheduling, sub-hourly time resolution, and stochastic effects due to uncertain weather or electricity price forecasts. This paper proposes a methodology to reduce the computational burden associated with simulation of electricity yield and revenue for CSP plants over a single- or multi-year period. Data-clustering techniques are employed to select a small number of limited-duration time blocks for simulation that, when appropriately weighted, can reproduce generation and revenue over a single year or within each year of a multi-year period. After selection of appropriate data features and weighting factors defining similarity between time-series profiles, the methodology captured annual revenue within 2.3%, 1.7%, or 1.2% using simulation of 10, 30, or 50 three-day exemplar time blocks, respectively, for each of three single-year location/weather/market scenarios and five plant configurations ranging from low to high solar multiple and storage capacity. When applied to multi-year datasets, the proposed methodology can capture inter-year variability that is unavailable from typical meteorological year (TMY) datasets while simultaneously requiring simulation of less than a single year of data.

14 SOLAR ENERGY↗