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At least 505 records · Page 28

Model checking

Automatic formal verification methods for finite-state systems, also known as model-checking, successfully reduce labor costs since they are mostly automatic. Model checkers explicitly or implicitly enumerate the reachable state space of a system, whose behavior is described implicitly, perhaps by a program or a collection of finite automata. Simple properties, such as mutual exclusion or absence of deadlock, can be checked by inspecting individual states. More complex properties, such as lack of starvation, require search for cycles in the state graph with particular properties. Specifications to be checked may consist of built-in properties, such as deadlock or 'unspecified receptions' of messages, another program or implicit description, to be compared with a simulation, bisimulation, or language inclusion relation, or an assertion in one of several temporal logics. Finite-state verification tools are beginning to have a significant impact in commercial designs. There are many success stories of verification tools finding bugs in protocols or hardware controllers. In some cases, these tools have been incorporated into design methodology. Research in finite-state verification has been advancing rapidly, and is showing no signs of slowing down. Recent results include probabilistic algorithms for verification, exploitation of symmetry and independent events, and the use symbolic representations for Boolean functions and systems of linear inequalities. One of the most exciting areas for further research is the combination of model-checking with theorem-proving methods.

Dill, David L.↗

Object-Oriented Control System Design Using On-Line Training of Artificial Neural Networks

This report deals with the object-oriented model development of a neuro-controller design for permanent magnet (PM) dc motor drives. The system under study is described as a collection of interacting objects. Each object module describes the object behaviors, called methods. The characteristics of the object are included in its variables. The knowledge of the object exists within its variables, and the performance is determined by its methods. This structure maps well to the real world objects that comprise the system being modeled. A dynamic learning architecture that possesses the capabilities of simultaneous on-line identification and control is incorporated to enforce constraints on connections and control the dynamics of the motor. The control action is implemented "on-line", in "real time" in such a way that the predicted trajectory follows a specified reference model. A design example of controlling a PM dc motor drive on-line shows the effectiveness of the design tool. This will therefore be very useful in aerospace applications. It is expected to provide an innovative and noval software model for the rocket engine numerical simulator executive.

Rubaai, Ahmed↗

Aberrations in Fresnel Lenses and Mirrors

The NASA/MSFC Shooting Star program revealed a number of technical problems that must be solved before solar thermal propulsion can become a reality. The fundamental problem of interest here is the collection of solar energy. This is the first step in the propulsion process and indeed the most important. Everything else depends on the efficiency and focusing ability of the collection lens or mirror. An initial model of Fresnel lens behavior using a wave optics approach has been completed and the results were encouraging enough to warrant an experimental investigation. This experimental investigation confirmed some of the effects predicted and produced invaluable photographic evidence of coherence based diffraction and aberration.

Gregory, Don↗

Microwave Signatures of Melting/Refreezing Snow: Observations and Modeling Using Dense Medium Radiative Transfer Theory

Microwave brightness temperatures of snow covered terrains can be modeled by means of the Dense Radiative Transfer Medium Theory (DMRT). In a dense medium, such as snow, the assumption of independent scattering is no longer valid and the scattering of correlated scatterers must be considered. In the DMRT, this is done considering a pair distribution function of the particles position. In the electromagnetic model, the snowpack is simulated as a homogeneous layer having effective permittivity and albedo calculated through the DMRT. In order to account for clustering of snow crystals, a model of cohesive particles can be applied, where the cohesion between the particles is described by means of a dimensionless parameters called stickiness (z), representing a measure of the inversion of the attraction of the particles. The lower the z the higher the stickiness. In this study, microwave signatures of melting and refreezing cycles of seasonal snowpacks at high altitudes are studied by means of both experimental and modeling tools. Radiometric data were collected 24 hours per day by the University of Michigan Tower Mounted Radiometer System (TMRS). The brightness temperatures collected by means of the TMRS are simulated by means of a multi-layer electromagnetic model based on the dense medium theory with the inputs to the model derived from the data collected at the snow pits and from the meteorological station. The paper is structured as follows: in the first Section the temperature profiles recorded by the meteorological station and the snow pit data are presented and analyzed; in the second Section, the characteristics of the radiometric system used to collect the brightness temperatures are reported together with the temporal behavior of the recorded brightness temperatures; in the successive Section the multi-layer DMRT-based electromagnetic model is described; in the fourth Section the comparison between modeled and measured brightness temperatures is discussed. We dedicate the last Section to the conclusions and future works.

Tedesco, Marco↗

Overview of Plume-Surface Interaction Data from Subscale Inert Gas Testing at NASA MSFC Test Stand 300 Vacuum Facilities

Maturation and validation of predictive modeling capabilities for plume-surface interaction, and the effects caused by the impingement of rocket engine exhaust on surface regolith, require relevant, highly characterized ground test data. The multi-phase nature of this problem poses challenges to ground testing across physical scaling, test environments and techniques, and diagnostics. NASA has developed a Physics Focused Ground Test (PFGT) of plume-surface interaction to address this need. The PFGT is a subscale, inert-gas experiment at Mars- and Lunar-relevant ambient pressure conditions that will provide critical data for model validation of cratering, ejecta, and plume physics. In this test, the ambient pressure in a vacuum chamber will be varied, along with the height of a supersonic nozzle above a surface, and the mass flow rate through the nozzle. Testing will be performed on a range of regolith simulants of varying composition and will also include instrumented impingement plate tests in place of regolith simulant to characterize gas-only plume physics. Novel high-speed visual diagnostics will capture temporal data on crater formation and ejecta dynamics, and planar laser-induced fluorescence diagnostics will capture plume structure and behavior. This paper will present an overview of the data collected during this test – for both the cratering and ejecta testing and the gas-only plume physics testing. Emphasis will be placed on trends, effects, and interactions observed in the data across the test parameter space.

Chad J. Eberhart↗

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗

Coupling Microstructural Evolution Simulations to Material Property Degradation Predictions for Plasma-Facing Materials

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

Connect microstructure evolution to property degradation with validated simulation

Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500$^o$C to 1500$^o$C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 $\frac{D}{m^2s}$. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.

36 - MATERIALS SCIENCE↗

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

Waller, M. C.↗

Experimentation Toward the Analysis of Gear Noise Sources Controlled by Sliding Friction and Surface Roughness

In helicopters and other rotorcraft, the gearbox is a major source of noise and vibration (N&V). The two N&V excitation mechanisms are the relative displacements between mating gears (transmission errors) and the friction associated with sliding between gear teeth. Historically, transmission errors have been minimized via improved manufacturing accuracies and tooth modifications. Yet, at high torque loads, noise levels are still relatively high though transmission errors might be somewhat minimal. This suggests that sliding friction is indeed a dominant noise source for high power density rotorcraft gearboxes. In reality, friction source mechanism is associated with surface roughness, lubrication regime properties, time-varying friction forces/torques and gear-mesh interface dynamics. Currently, the nature of these mechanisms is not well understood, while there is a definite need for analytical tools that incorporate sliding resistance and surface roughness, and predict their effects on the vibro- acoustic behavior of gears. Toward this end, an experiment was conducted to collect sound and vibration data on the NASA Glenn Gear-Noise Rig. Three iterations of the experiment were accomplished: Iteration 1 tested a baseline set of gears to establish a benchmark. Iteration 2 used a gear-set with low surface asperities to reduce the sliding friction excitation. Iteration 3 incorporated low viscosity oil with the baseline set of gears to examine the effect of lubrication. The results from this experiment will contribute to a two year project in collaboration with the Ohio State University to develop the necessary mathematical and computer models for analyzing geared systems and explain key physical phenomena seen in experiments. Given the importance of sliding friction in the gear dynamic and vibro-acoustic behavior of rotorcraft gearboxes, there is considerable potential for research & developmental activities. Better models and understanding will lead to quiet and reliable gear designs, as well as the selection of optimal manufacturing processes.

Asnani, Vivake M.↗

Status of the Terra and Aqua Modis Collection 7 L1B

The MODIS instruments on the Terra and Aqua spacecrafts have successfully operated for more than 23 and 21years, respectively, and have far exceeded their designed lifetimes of 6 years. The visible, near infrared, and short-wave infrared spectral bands, with wavelengths from 0.41 to 2.2 μm, are calibrated using the on-board solar diffuser. Themid-wave infrared and long-wave infrared spectral bands are calibrated using a blackbody. The sustained calibration and characterization efforts undertaken by the MODIS Characterization Support Team (MCST) have resulted in several upgrades to the Level-1B (L1B) algorithms over the mission lifetime. The latest version of the L1B algorithm, designated as Collection 7 (C7), was developed based upon observed performance of the current operational L1B product (C6.1), changing instrument behavior, and feedback from the science community. This paper provides an overview of the C7 algorithm and its improvements over the previous data collection, as well as some of the updates that have been incorporated since the first delivery in early 2021.

Amit Angal↗

A channel flow cell with double disk electrodes for oxygen electroreduction study at elevated temperatures and pressures: Theory

We report a new double-disk-electrode channel flow cell has been designed, constructed and tested. A theoretical treatment and implicit finite difference numerical simulations are presented, which permit the computation of the hydrodynamic behavior of this cell under steady state conditions, i.e., the diffusion limited current at the working electrode and the collection efficiency of the detector. The simulated results are consistent with those measured experimentally, indicating that our simulations appropriately describe the hydrodynamic behavior of this cell. The oxygen reduction reaction (ORR) on a carbon-supported nanoparticle Pt catalyst at both room temperature and 110 °C were preliminarily studied with this cell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Interfacial Adhesion Mechanism of Anionic Polyelectrolyte Brushes Induced by Oppositely Charged Macromolecular Counterions

Abstract Polyelectrolyte brushes are widely used as model systems for investigating electrostatic interactions at soft interfaces and to achieve exceptional lubrication properties. Previous studies have primarily focused on their behavior in the presence of multivalent counterions, which induce brush collapse, ionic crosslinking, and pronounced changes in interfacial structures. However, interactions between polyelectrolyte brushes and oppositely charged macromolecular counterions, such as polycations, remain poorly understood. Here, we prepare well-defined polystyrene sulfonate (PSS) brushes fabricated via surface-initiated grafting and employ surface forces apparatus measurements to investigate their interactions with oppositely charged polycations. In contrast to multivalent ions, polycations do not induce noticeable brush collapse, but instead generate significant adhesion between symmetric PSS brush layers. This adhesion increases with both contact time and applied load, eventually reaching a steady plateau, indicating that the interaction is governed not simply by electrostatic screening but by the gradual formation of polycation-mediated bridging under confinement. Furthermore, the introduction of monovalent Na+ ions disrupts the adhesive interaction even at very low concentrations, suggesting that the bridging function of the adsorbed polycation is highly sensitive to competitive ionic screening. In comparison, measurements with trivalent counterions reveal the expected brush collapse behavior but minimal dependence of adhesion on contact time, highlighting a clear mechanistic distinction from the polymeric counterion case. Collectively, these results demonstrate that molecular size, configurational restriction, and confinement-induced rearrangement, rather than charge valency alone, govern the interaction behavior of macromolecular counterions at brush interfaces. This work provides new insight into the molecular origins of adhesion and the regulation of interfacial interactions in charged polymer brush systems.

Park, Jinwoo [Argonne National Laboratory , , , ,;↗

Relationships between maternally-transferred mercury and hatchling development, behavior, and survival in the American alligator ( Alligator mississippiensis )

Mercury is a toxic and pervasive environmental contaminant that can be transferred from mother to offspring during development. Consequences of maternally-transferred mercury have been observed in vertebrate taxa, including reduced clutch viability, reduced offspring size, and behavioral alterations. These sublethal effects have been assumed to decrease survivorship, though this is seldom assessed. Here, we examined how maternally-transferred mercury interacts with incubation temperature to influence reproductive success, offspring behavior, and subsequent survival in the American alligator (Alligator mississippiensis). We collected nine clutches of eggs from a mercury contaminated reservoir on the Savannah River Site, South Carolina, and incubated eggs at either female- or male-promoting temperatures. Clutch-averaged mercury in egg yolk was high relative to other studies in crocodilians and ranged from 0.248 to 0.554 ppm compared to 0.018–0.052 ppm at a site with low levels of mercury contamination; mercury levels in hatchling blood ranged from 0.090 to 0.490 ppm ($\overline{x}$= 0.240 ppm, n = 158). We found few, mostly negligible correlations between life history traits and mercury but noted a positive relationship with egg mass, possibly mediated by correlated maternal effects such as resource provisioning. Incubation temperature exerted strong effects on hatchling phenotypes, with warmer, male-promoting temperatures producing larger and bolder hatchlings. Presumptive females, produced from cooler incubation temperatures, spent more time in warm areas during behavior trials. Hatchlings were released 10–15 days post-hatch and surveyed over eight months to assess survival. Survivorship was positively correlated with hatchling size and negatively correlated with proportional time spent in warm areas. Presumptive females had much lower survival, and overall survivorship for the eight-month period was 0.185–0.208, depending on the modelling approach. Finally, our study suggests that, within the range of concentrations we observed, incubation temperature has a stronger effect on offspring behavior and survival than maternally-transferred mercury pollution in American alligators.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal Growth of Quaternary RE 2 EuSi 2 S 8 ( RE = Ce–Nd, Sm, Gd, Tb) Using Flux-Assisted Boron Chalcogen Mixture (BCM) Method: Investigation of Magnetic and Luminescence Properties

A series of quaternary rare-earth containing thiosilicates with the general formula RE 2 EuSi 2 S 8 (RE = Ce–Nd, Sm, Gd, Tb) has been synthesized via the flux-assisted boron chalcogen mixture (BCM) crystal growth method. High-quality single crystals were obtained, and their crystal structures were determined by single-crystal X-ray diffraction. The RE 2 EuSi 2 S 8 series crystallizes in the trigonal system, adopting the space group R-3c. Polycrystalline samples were employed for physical property measurements, including magnetic susceptibility measurements, UV–visible diffuse reflectance, and photoluminescent response. Magnetic data of RE 2 EuSi 2 S 8 ( RE = Ce, Nd, and Gd) were collected over the 2–300 K temperature range. The samples were paramagnetic behavior with negative Weiss constants (θ W = −11.05, −10.55, and −1.35 K respectively). Their thermal stability was investigated using thermogravimetric analysis (TGA). Optical band gaps, estimated from diffuse reflectance spectra, were determined to be 2.2(1) eV for Ce 2 EuSi 2 S 8 , 1.8(1) eV for Nd 2 EuSi 2 S 8 , and 1.7(1) eV for Gd 2 EuSi 2 S 8 respectively. Finally, photoluminescence measurements were collected on Ce 2 EuSi 2 S 8 and Tb 2 EuSi 2 S 8 single crystals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Behavior of Typically Lithophile Elements Under Highly Reducing Conditions Relevant to the Planet Mercury

With the data returned from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) mission, there are now numerous constraints on the physical and chemical properties of Mercury, including its surface composition (e.g., Evans et al. 2012; Nittler et al. 201 l; Peplowski et al. 2012; Weider et al. 2012). The high Sand low FeO contents observed from MESSENGER on the planet's surface suggests a low oxygen fugacity of the present planetary materials. Estimates of the oxygen fugacity for Mercurian magmas are approximately 3- 7 log units below the Iron-Wiistite (Fe-FeO) oxygen buffer (McCubbin et al. 2012; Zolotov et al. 2013), several orders of magnitude more reducing than other terrestrial bodies we have data from such as the Earth, Moon, or Mars (Herd 2008; Sharp, McCubbin, and Shearer 2013; Wadhwa 2008). Most of our understanding of elemental partitioning behavior comes from observations made on terrestrial rocks, but Mercury's oxygen fugacity is far outside the conditions of those samples. With limited oxygen available, lithophile elements may instead exhibit chalcophile, halophile, or siderophile behaviors. Furthermore, very few natural samples of rocks that formed under reducing conditions are available in our collections (e.g., enstatite chondrites, achondrites, aubrites). The goal of this study is to conduct experiments at high pressure and temperature conditions to determine the elemental partitioning behavior of typically lithophile elements as a function of decreasing oxygen fugacity.

Rowland, Rick, II↗

FY23 Post-LOCA Characterization of Irradiated Fuel (NSUF Award 17-12985)

This report summarizes the sample preparation and data collection on fuel pins following integral LOCA testing in the Severe Accident Test Station at Oak Ridge National Laboratory. The test sample cross-sections show post-transient fragmentation behavior of UO 2 commercially irradiated above 67 MWd/kgU. Ring compression testing and hydrogen measurements were collected on the cladding segments.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

1994 SEMCOG Household-Based Person Trip Survey

The Southeast Michigan Council of Governments contracted with the Applied Management & Planning Group to conduct a travel behavior survey of 7,361 households from March 28, 1994, to June 10, 1994. The primary purpose of this study was to provide the council with a new database of travel behavior to assist in updating the region's transportation models. This data collection includes demographic, socioeconomic, travel, and mobile source emissions models for projecting future patterns of development, travel, congestion, and air pollution. Information about household characteristics and travel was collected using a one-day, activity-focused diary and a separate household survey. In an activity diary, respondents recorded 65,535 trips during the assigned the day.

1Hz data↗