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

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At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2002

Semicarbazide-sensitive amine oxidase and extracellular matrix deposition by smooth-muscle cells

We have recently reported in vivo disruption of collagen and elastin architecture within blood vessel walls resulting from the selective inhibition of the enzyme semicarbazide-sensitive amine oxidase (SSAO). This study further investigates the effects of SSAO inhibition on extracellular matrix deposition by smooth-muscle cells (SMCs) cultured from neonatal rat hearts. SMCs were characterized, SSAO activity was measured, and soluble and insoluble collagen and elastin in the extracellular matrix (ECM) were quantified. Cultured neonatal rat heart SMC exhibited a monotypic synthetic phenotype that likely represents a myofibroblast. Detectable levels of SSAO activity present throughout 30-d culture peaked at 7-14 d, coinciding with the production of ECM. The addition of enzyme inhibitors and alternate SSAO substrates (benzylamine) produced varied and, in some cases, marked changes in SSAO activity as well as in the composition of mature and soluble matrix components. Similar to our previous in vivo findings, in vitro SSAO inhibition produced aberrations in collagen and elastin deposition by heart SMC. Because changes in SSAO activity are associated with cardiovascular pathologic states, this enzyme may play a protective or modulating role by regulating ECM production during pathologic insult.

Allylamine/administration & dosage/analogs & deriv↗
NASA NTRS1990

Fueling active galactic nuclei by magnetic braking

Recent detections of massive concentrations of molecular gas near the centers of galaxies hosting active nuclei suggest that these concentrations may be the source of accretion fuel for the nucleus. However, for that to be true, an angular momentum barrier must be overcome before the material in such a cloud can reach the nucleus. It is suggested that magnetic braking of the cloud may remove sufficient angular momentum to permit its material to draw considerably closer to the central object. The mechanism is particularly effective in the limit that the gas becomes self-gravitating because removal of a fraction of the initial angular momentum can lead to dynamical instability and collapse. Any small misalignment between the initial rotation axis of the cloud and the rotation axis of the galaxy can be substantially amplified as a result of the braking. It is argued that mass accretion onto the central object may occur in episodes, in some cases with a constant mass accretion rate during each episode.

Krolik, Julian H.↗
NASA NTRS2020

The Lowest-frequency Fast Radio Bursts: Sardinia Radio Telescope Detection of the Periodic FRB 180916 at 328 MHz

We report on the lowest-frequency detection to date of three bursts from the fast radio burst FRB 180916.J0158+65, observed at 328 MHz with the Sardinia Radio Telescope (SRT). The SRT observed the periodic repeater FRB 180916.J0158+65 for five days from 2020 February 20 to 24 during a time interval of active radio bursting, and detected the three bursts during the first hour of observations; no more bursts were detected during the remaining ∼30 hr. Simultaneous SRT observations at 1548 MHz did not detect any bursts. Burst fluences are in the range 37 to 13 Jy ms. No relevant scattering is observed for these bursts. We also present the results of the multiwavelength campaign we performed on FRB 180916.J0158+65, during the five days of the active window. Simultaneously with the SRT observations, others with different time spans were performed with the Northern Cross at 408 MHz, with XMM-Newton, NICER, INTEGRAL, AGILE, and with the TNG and two optical telescopes in Asiago, which are equipped with fast photometers. XMM-Newton obtained data simultaneously with the three bursts detected by the SRT, and determined a luminosity upper limit in the 0.3–10 keV energy range of ∼10(exp 45) erg/s for the burst emission. AGILE obtained data simultaneously with the first burst and determined a fluence upper limit in the MeV range for millisecond timescales of 10(exp -8) erg/sq.cm. Our results show that absorption from the circumburst medium does not significantly affect the emission from FRB 180916.J0158+65, thus limiting the possible presence of a superluminous supernova around the source, and indicate that a cutoff for the bursting mechanism, if present, must be at lower frequencies. Our multi-wavelength campaign sensitively constrains the broadband emission from FRB 180916.J0158+65, and provides the best limits so far for the electromagnetic response to the radio bursting of this remarkable source of fast radio bursts.

M. Pilia↗
NASA NTRS2000

Electromagnetic Waves and Bursty Electron Acceleration: Implications from Freja

Dispersive Alfven wave activity is identified in four dayside auroral oval events measured by the Freja satellite. The events are characterized by ion injection, bursty electron precipitation below about I keV, transverse ion heating and broadband extremely low frequency (ELF) emissions below the lower hybrid cutoff frequency (a few kHz). The broadband emissions are observed to become more electrostatic towards higher frequencies. Large-scale density depletions/cavities, as determined by the Langmuir probe measurements, and strong electrostatic emissions are often observed simultaneously. A correlation study has been carried out between the E- and B-field fluctuations below 64 Hz (the dc instrument's upper threshold) and the characteristics of the precipitating electrons. This study revealed that the energization of electrons is indeed related to the broadband ELF emissions and that the electrostatic component plays a predominant role during very active magnetospheric conditions. Furthermore, the effect of the ELF electromagnetic emissions on the larger scale field-aligned current systems has been investigated, and it is found that such an effect cannot be detected. Instead, the Alfvenic activity creates a local region of field-aligned currents. It is suggested that dispersive Alfven waves set up these local field-aligned current regions and in turn trigger more electrostatic emissions during certain conditions. In these regions ions are transversely heated, and large-scale density depletions/cavities may be created during especially active periods.

Andersson, Laila↗
DOE OSTI2012

Passive Acoustic Detection of Wind Turbine In-Flow Conditions for Active Control and Optimization

Wind is a significant source of energy; however, the human capability to produce electrical energy still has many hurdles to overcome. One of these is the unpredictability of the winds in the atmospheric boundary layer (ABL). The ABL is highly turbulent in both stable and unstable conditions (based on the vertical temperature profile) and the resulting fluctuations can have a dramatic impact on wind turbine operation. Any method by which these fluctuations could be observed, estimated, or predicted could provide a benefit to the wind energy industry as a whole. Based on the fundamental coupling of velocity fluctuations to pressure fluctuations in the nearly incompressible flow in the ABL, This work hypothesizes that a ground-based array of infrasonic pressure transducers could be employed to estimate the vertical wind profile over a height relevant for wind turbines. To analyze this hypothesis, experiments and field deployments were conducted. Wind tunnel experiments were performed for a thick turbulent boundary layer over a neutral or heated surface. Surface pressure and velocity probe measurements were acquired simultaneously. Two field deployments yielded surface pressure data from a 49 element array. The second deployment at the Reese Technology Center in Lubbock, TX, also included data from a smaller aperture, 96-element array and a 200-meter tall meteorological tower. Analysis of the data successfully demonstrated the ability to estimate the vertical velocity profile using coherence data from the pressure array. Also, dynamical systems analysis methods were successful in identifying and tracking a gust type event. In addition to the passive acoustic profiling method, this program also investigated a rapid response Doppler SODAR system, the optimization of wind turbine blades for enhanced power with reduced aeroacoustic noise production, and the implementation of a wireless health monitoring system for the wind turbine blades. Each of these other objectives was met successfully. The use of phase unwrapping applied to SODAR data was found to yield reasonable results for per-pulse measurements. A health monitoring system design analysis was able to demonstrate the ability to use a very small number of sensors to monitor blade health based on the blade's overall structural modes. Most notable was the development of a multi-objective optimization methodology that successfully yielded an aerodynamic blade design that produces greater power output with reduced aerodynamic loading noise. This optimization method could be significant for future design work.

17 WIND ENERGY↗
DOE OSTI2016

Using Machine Learning in Adversarial Environments.

Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approaches only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

Saturn Magnetospheric Impact on Surface Molecular Chemistry and Astrobiological Potential of Enceladus

The active south polar surface of Enceladus is exposed to strong chemical processing by direct interaction with charged plasma and energetic particles in the local magnetospheric environment of this icy moon. Chemical oxidation activity is suggested by detection of H202 at the surface in this region and less directly by substantial presence of C02, CO, and N2 in the plume gases. Molecular composition of the uppermost surface, including ejecta from plume activity, is radiolytically transformed mostly by penetrating energetic electrons with lesser effects from more depleted populations of energetic protons. The main sources of molecular plasma ions and E-ring dust grains in the magnetospheric environment are the cryovolcanic plume emissions from Enceladus. These molecular ions and the dust grains are chemically processed by magnetospheric interactions that further impact surface chemistry on return to Enceladus. For example, H20 neutrals dominating the emitted plume gas return to the surface mostly as H30+ ions after magnetospheric processing. Surface oxidant loading is further increased by return of radiolytically processed ice grains from the E-ring. Plume frost deposition and micrometeoroid gardening protect some fraction of newly produced molecular species from destruction by further irradiation. The evident horizontal and vertical mobility of surface ices in the south polar region drive mixing of these processed materials into the moon interior with potential impacts on deep ice molecular chemistry and plume gas production. Similarly as suggested previously for Europa, the externally driven source of radiolytic oxidants could affect evolution of life in any subsurface liquid water environments of Enceladus.

Cooper, Paul D.↗
DOE OSTI2021

EXPRES. II. Searching for Planets around Active Stars: A Case Study of HD 101501

By controlling instrumental errors to below 10 cm s{sup −1}, the EXtreme PREcision Spectrograph (EXPRES) allows for a more insightful study of photospheric velocities that can mask weak Keplerian signals. Gaussian processes (GP) have become a standard tool for modeling correlated noise in radial velocity data sets. While GPs are constrained and motivated by physical properties of the star, in some cases they are still flexible enough to absorb unresolved Keplerian signals. We apply GP regression to EXPRES radial velocity measurements of the 3.5 Gyr old chromospherically active Sun-like star, HD 101501. We obtain tight constraints on the stellar rotation period and the evolution of spot distributions using 28 seasons of ground-based photometry, as well as recent Transiting Exoplanet Survey Satellite data. Light-curve inversion was carried out on both photometry data sets to reveal the spot distribution and spot evolution timescales on the star. We find that the >5 m s{sup −1} rms radial velocity variations in HD 101501 are well modeled with a GP stellar activity model without planets, yielding a residual rms scatter of 45 cm s{sup −1}. We carry out simulations, injecting and recovering signals with the GP framework, to demonstrate that high-cadence observations are required to use GPs most efficiently to detect low-mass planets around active stars like HD 101501. Sparse sampling prevents GPs from learning the correlated noise structure and can allow it to absorb prospective Keplerian signals. We quantify the moderate to high-cadence monitoring that provides the necessary information to disentangle photospheric features using GPs and to detect planets around active stars.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Prototype System for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and equipment out of service would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify the incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment that is being relied on to meet the requirements of the nuclear safety plan. In addition, Operations and the Outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently in outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This project will develop tools and strategies to minimize these interactions. This report describes a prototype tool designed to support plant personnel in controlling work during NPP outages to prevent unintended interactions. A software application was created to manage and display important configuration information and utilize natural language processing to access the impacts of upcoming procedures and work orders. Initial industry feedback is also presented.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2019

Methods to Automate Assessing the Outage Risk and Technical Specification Compliance for Planned Work and Current Plant Conditions. Light Water Reactor Sustainability Program report

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and the extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages. This is done through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and out of service equipment would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment necessary to meet the requirements of the nuclear safety plan. In addition, the operations and outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently during outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This particular report will provide a demonstration of the capabilities in the development of a predictive software platform for improving configuration control and accessing the plant risks associated with outage work protocols and illustrate how the software assists in strategies to minimize these interactions. In addition to maintaining nuclear safety, there are numerous administrative requirements that must be complied with during an outage. This report will discuss the use of logic modelling to monitor planned work against technical specification requirements for given plant conditions and to integrate these requirements with shutdown risk models, clearance order requirements and other plant condition requirements.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Technologies for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and extension of their current operating licenses. A new area of LWRS research, Outage Risk Management Improvement (ORMI) seeks to improve the management of nuclear power plant outages through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and equipment out of service would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify the incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment that is being relied on to meet the requirements of the nuclear safety plan. In addition, Operations and the Outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently in outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This project will develop tools and strategies to minimize these interactions.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1990

Immunological characterization of plant ornithine transcarbamylases

Pea (Pisum sativum L.) ornithine transcarbamylase (OTC) antisera were used to investigate the immunological relatedness of several plant and animal OTC enzymes. The antisera immunoprecipitated OTC activity in all monocot and dicot species tested, and sodium dodecyl sulfate polyacrylamide gel electrophoresis analysis of immunoprecipitated protein revealed monomeric proteins ranging from 35,200 to 36,800 daltons in size. Pea OTC antisera did not recognize mammalian OTC protein. OTC activity and protein levels detected on sodium dodecyl sulfate polyacrylamide gel electrophoresis immunoblots from homogenates of green leaf, etiolated epicotyl and cotyledon, and root tissues of pea were poorly correlated. This might result from differences in amounts of enzymatically active OTC protein in the homogenates. Alternatively, the antisera may fail to recognize different isozyme forms of OTC, which have been reported for some plant species. A putative cytosolic precursor OTC (pOTC) polypeptide exhibiting and Mr = 39,500 to 40,000 daltons was immunoprecipitated from in vitro translation mixtures of total pea leaf poly(A)+ RNA. The size of the pOTC polypeptide, as compared with mature OTC monomer (36,000 daltons), suggests that a 4 kilodalton N-terminal leader sequence, like that responsible for mitochondrial targeting of the mammalian enzyme, may be involved in organellar import of the plant enzyme.

NASA Discipline Plant Biology↗
DOE OSTI2017

Integrated Nondestructive Assay Systems to Estimate Plutonium in Spent Fuel Assemblies

An integrated nondestructive assay (NDA) system combining active (neutron generator) and passive neutron detection and passive gamma (PG) detection is being analyzed in order to estimate the amount of plutonium, verify initial enrichment, burnup, and cooling time, and detect partial defects in a spent fuel assembly (SFA). Active signals are measured using the differential die-away (DDA), delayed neutron (DN), and delayed gamma (DG) techniques. Passive signals are measured using total neutron (TN) counts and both gross and spectral resolved gamma counts. To quantify how a system of several NDA techniques is expected to perform, all of the relevant NDA techniques listed above were simulated as a function of various reactor conditions such as initial enrichment, burnup, cooling time, assembly shuffling pattern, reactor operating conditions (including temperature, pressure, and the presence of burnable poisons) by simulating the NDA response for five sets of light water reactor assemblies. In this study, we compare the performance of several exploratory model-fitting options (including neural networks, adaptive regression with splines, iterative bias reduction smoothing, projection pursuit regression, and regression with quadratic terms and interaction terms) to relate data simulated with measurement and model error effects from various subsets of the NDA techniques to the total Pu mass. Isotope masses for SFAs and expected detector responses (DRs) for several NDA techniques are simulated using MCNP, and the DRs become inputs to the fitting process. Such responses include eight signals from DDA, one from DN, one from TN, and up to seven from PG; the DG signal will be examined separately. Results are summarized using the root-mean-squared estimation error for plutonium mass in held-out subsets of the data for a range of model and measurement error variances. Different simulation assumptions lead to different spent fuel libraries relating DRs to Pu mass. Some results for training with one library and testing with another library are also given.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Identification of Faults Susceptible to Induced Seismicity (Final Report)

Central to the work documented in this report is the capability of geocellular models to represent the geologic conceptual model updated with fault identification from machine learning and joint inversion modeling of microseismic data measured and recorded as a consequence of CO 2 injection at a field demonstration site: the Illinois Basin - Decatur Project (IBDP). This work required seven unique geocellular models with 100s of simulated variations to gain a very high degree of confidence in the identification of geologic features present that contributed to induced microseismicity at IBDP. All forward modeling: pressure modeling, stress modeling, and seismic modeling used the same geologic conceptual model and representations of that model at different scales. The pressure modeling and poroelastic modeling created “snapshots” of pore pressure and stress field changes at different times during CO 2 injection, in which microseismic events were clustered (in time). These pressure and stress snapshots, within the framework and architecture of the geologic conceptual model via the geocellular model, informed the single fault and fault network models to ascertain the likelihood of fault movement (seismic or aseismic). The outcomes of the pressure, stress, and fault/fault network (seismic) modeling confirmed that the faults in the geologic conceptual model in Task 2 were likely the source of microseismic events measured at IBDP and acted as conduits for pressure to be transmitted from the injection interval into the Precambrian crystalline basement rock. This closely coordinated and integrated unique modeling approach was conducted to prove the viability of our proposed workflow 1) to better resolve crystalline basement faults, 2) detect subseismic faults that could be activated by injection, 3) increase the certainty in fault detection and their susceptibility to release seismic energy, and 4) understand transmission of pressure vertically from the well to the underlying fractured crystalline basement. The proposed methodology was effective in guiding an iterative process of calibrating forward modeling results based on similar geocellular models while honoring the geologic conceptual model (i.e., characterization data and knowledge of regional geology); this led to higher level of certainty in the identification of fault/faults zones to control seismicity and transmission of pressure to the regions of recorded and located injection induced seismicity.

58 GEOSCIENCES↗
NASA NTRS1982

Results of the IUE program of monitoring the ultraviolet emission line fluxes of four binary systems: HR 1099, 2 Peg, AR Lac and By Dra

A program to obtain IUE spectra and optical photometry and spectra of three RS CVn-type binaries (HR 1099, II Peg, and AR Lac) and the prototype BY Dra system is reported. The systems were monitored for at least one orbital phase, and periodic variations in emission line flux from II Peg and HR 1099, indicative of notational modulation of an active region on these stars were detected. It is found that for II Peg the active region is in phase with photometric minimum as expected, but for HR 1099 ultraviolet emission maximum occurs at the time of photometric maximum.

Marstad, M.↗