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Hydrodynamic model of screen channel liquid acquisition devices for in-space cryogenic propellant management
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FEDERATED LEARNING ON STOCHASTIC NEURAL NETWORKS
Federated learning is a machine learning paradigm that leverages edge computing on client devices to optimize models while maintaining user privacy by ensuring that local data remain on the device. However, since all data are collected by clients, federated learning is susceptible to latent noise in local datasets. Factors such as limited measurement capabilities or human errors may introduce inaccuracies in client data. To address this challenge, we propose the use of a stochastic neural network as the local model within the federated learning framework. Stochastic neural networks not only facilitate the estimation of the true underlying states of the data but also enable the quantification of latent noise. We refer to our federated learning approach, which incorporates stochastic neural networks as local models, as federated stochastic neural networks. In this work we will present numerical experiments demonstrating the performance and effectiveness of our method, particularly in handling nonindependent and identically distributed data.
Real-time interface investigation on degradation mechanism of organic light-emitting diode by in-operando X-ray spectroscopies
Understanding the chemical evolution at the interface of organic light-emitting diodes (OLEDs) under working conditions is critical for addressing device failure and further improving performance. In this work, an in-operando approach was developed employing synchrotron-based X-ray absorption spectroscopy (XAS) to investigate the electronic structures and chemical degradation mechanisms of a model tris(8-hydroxyquinoline) aluminum (Alq 3 )-based OLED device under working condition. The results identify that Mg atoms from the electrode migrate into the Alq 3 organic layer under a potential bias and replace Al atom sites, forming the unstable Mgq 3 species which lead to device degradation. Here, the findings from the classic and simple model device elucidate the degradation mechanisms occurred at the interface of OLED devices, which may facilitate the development of more efficient and stable OLED devices with complex structures.
Z 3 Parafermion in the Double Charge Kondo Model
Quantum impurity models with frustrated Kondo interactions can support quantum critical points with fractionalized excitations. Recent experiments [arXiv:2108.12691] on a circuit containing two coupled metal-semiconductor islands exhibit transport signatures of such a critical point. Here we show using bosonization that the double charge-Kondo model describing the device can be mapped in the Toulouse limit to a sine-Gordon model. Its Bethe-ansatz solution shows that a Z 3 parafermion emerges at the critical point, characterized by a fractional $\frac{1}{2}$ln(3) residual entropy, and scattering fractional charges e/3. Finally, we also present full numerical renormalization group calculations for the model and show that the predicted behavior of conductance is consistent with experimental results.
SICAS, a new integrated divertor-SOL-pedestal-core framework for self-consistent modeling of ion and impurity transport in fusion devices
We present a new framework for core-edge integration studies named SICAS (SOLPS-ITER coupled to ASTRA-STRAHL) which enables high fidelity simulations of the core, edge, and divertor regions encompassing the transport of ions as well as the impurities through the entire plasma domain. SICAS handles the exchanging of the particle and power fluxes as well as transport coefficients to ensure consistency through the codes. An overlapping region is defined from the inside of the separatrix of the plasma to the SOLPS-ITER core boundary allowing for matching profiles and fluxes between the two codes for a self-consistent approach. The results presented here demonstrated the flexibility of SICAS to simulate different configurations, scenarios, divertor geometries, and plasma species with good agreement with DIII-D experimental data. This tool opens new possibilities in integrated modeling of fusion devices integrating all relevant phenomena in the core and the divertor plasmas. These capabilities are required for the interpretation of current experiments as well as the design of new devices.
Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition
Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.
Iced Aircraft Flight Data for Flight Simulator Validation
NASA is developing and validating technology to incorporate aircraft icing effects into a flight training device concept demonstrator. Flight simulation models of a DHC-6 Twin Otter were developed from wind tunnel data using a subscale, complete aircraft model with and without simulated ice, and from previously acquired flight data. The validation of the simulation models required additional aircraft response time histories of the airplane configured with simulated ice similar to the subscale model testing. Therefore, a flight test was conducted using the NASA Twin Otter Icing Research Aircraft. Over 500 maneuvers of various types were conducted in this flight test. The validation data consisted of aircraft state parameters, pilot inputs, propulsion, weight, center of gravity, and moments of inertia with the airplane configured with different amounts of simulated ice. Emphasis was made to acquire data at wing stall and tailplane stall since these events are of primary interest to model accurately in the flight training device. Analyses of several datasets are described regarding wing and tailplane stall. Key findings from these analyses are that the simulated wing ice shapes significantly reduced the C , max, while the simulated tail ice caused elevator control force anomalies and tailplane stall when flaps were deflected 30 deg or greater. This effectively reduced the safe operating margins between iced wing and iced tail stall as flap deflection and thrust were increased. This flight test demonstrated that the critical aspects to be modeled in the icing effects flight training device include: iced wing and tail stall speeds, flap and thrust effects, control forces, and control effectiveness.
Biomechanical Modeling of Split-leg Squat and Heel Raise on the Hybrid Ultimate Lifting Kit (HULK)
Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and musculoskeletal forces that occur during exercises performed on the prototype devices. Computational models currently use OpenSim software, an open source code for musculoskeletal modeling, with biomechanical input data from subjects for estimation of muscle and joint loads. Subjects are instrumented with reflective markers for motion capture data collection while exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device. Ground reaction force data is collected with force plates under the feet and device loading is recorded through load cells internal to the HULK. This data is input into the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the loads on the body. Multiple exercises are performed and evaluated during a test session such as a full squat, single leg squat, heel raise and dead lift. Variables for these exercises include applied device load, narrow or wide foot stance, slow or fast cadence and the harness or long bar interface between the test subject and the device. Data from free weights are compared to the resistively loaded exercise device. The focus of this presentation is to summarize the results from the single-leg squat and heel raise exercises performed during three sessions occurring in 2015. Differences in loading configuration, cadence and stance produce differences in kinematics, joint toques and force and muscle forces.
Soyuz Landing Reconstructions
Introduction: Recent data show a landing-attributed injury rate among Soyuz crew members to be higher than predicted in original certification analysis. New vehicles being developed for NASA are being certified using analytical tools to quantify injury risk. This assessment will provide data to allow the Agency to evaluate whether these tools are able to capture true injury risk and allow a comparison between Soyuz landings and upcoming vehicles. Methods: A finite element model (FEM) of the Soyuz descent module (DM) and its landing environment were developed to recreate Soyuz landing conditions. Occupant breakout models composed of the Soyuz seat and Sokol helmet were then developed to evaluate occupant response. These models included both anthropomorphic test device (ATD) and human body model (HBM) surrogates in three anthropometric sizes. A generalized distribution analysis of the Soyuz landing environment was performed using landing variable distributions from available literature. Results were used to identify trends in vehicle landing acceleration with landing conditions and to compare landing model injury risk predictions with those estimated in vehicle certification analysis. Next, historic Soyuz landings identified as inducing occupant injury during were reconstructed using the developed landing model and estimated landing conditions. Results and Discussion: This assessment demonstrated the capability of certification metrics, which include a combination of vehicle- and occupant-level injury risk analysis, to identify elevated injury risk landing conditions. However, the developed landing load predictions were limited by available vehicle and landing condition data. Additional data, particularly landing acceleration data specific to historic Soyuz landing conditions, would greatly enhance this assessment’s findings.
Thermoelectric Air/Soil Energy-Harvesting Device
A proposed thermoelectric device would exploit natural temperature differences between air and soil to harvest small amounts of electric energy. Because the air/soil temperature difference fluctuates between nighttime and daytime, it is almost never zero, and so there is almost always some energy available for harvesting. Unlike photovoltaic cells, the proposed device could operate in the absence of sunlight. Unlike a Stirling engine, which could be designed to extract energy from the air/soil temperature difference, the proposed device would contain no moving parts. The main attractive feature of the proposed device would be high reliability. In a typical application, this device would be used for low-power charging of a battery that would, in turn, supply high power at brief, infrequent intervals for operating an instrumentation package containing sensors and communication circuits. The device (see figure) would include a heat exchanger buried in soil and connected to a heat pipe extending up to a short distance above the ground surface. A thermoelectric microgenerator (TEMG) would be mounted on top of the heat pipe. The TEMG could be of an advanced type, now under development, that could maintain high (relative to prior thermoelectric generators) power densities at small temperature differentials. A heat exchanger exposed to the air would be mounted on top of the TEMG. It would not matter whether the air was warmer than the soil or the soil warmer than the air: as long as there was a nonzero temperature difference, heat would flow through the device and electricity would be generated. A study of factors that could affect the design and operation of the device has been performed. These factors include the thermal conductances of the soil, the components of the device, the contacts between the components of the device, and the interfaces between the heat exchangers and their environments. The study included experiments that were performed on a model of the device to demonstrate feasibility. Because a TEMG suitable for this device was not available, a brass dummy component having a known thermal conductance of 1.68 W/K was substituted for the TEMG in the models to enable measurement of heat flows. The model included a water-based heat pipe 30 in. (76.2 cm) long and 1 in. (2.54 cm) in diameter, wrapped with polyethylene insulation to reduce radial heat flow. Several different side heat exchangers were tested. On the basis of the measurements, it was predicted that if a prototype of the device were equipped with a TEMG, daily temperature fluctuations would cause its output power to fluctuate between 0 and about 0.1 mW, peaking to 0.35 mW during early afternoon.
Band to Band Tunneling (BBT) Induced Leakage Current Enhancement in Irradiated Fully Depleted SOI Devices
We propose a model, validated with simulations, describing how band-to-band tunneling (BBT) affects the leakage current degradation in some irradiated fully-depleted SOI devices. The dependence of drain current on gate voltage, including the apparent transition to a high current regime is explained.
TEXSYS - A large scale demonstration of model-based real-time control of a Space Station subsystem
A hybrid approach to qualitative and temporal reasoning, using a device-oriented model-based representation in conjunction with both consistency-based and classification diagnosis methods, can be effectively used to monitor and control a complex electromechanical system. An example of this approach is given in some recent tests of the Thermal Expert System (TEXSYS) in control of the Boeing Aerospace Thermal Bus System (BATBS), a prototype two-phase Space Station Freedom thermal bus. The constraints of realtime performance and changing target hardware led to significant changes in the initial approach, including a reduction in the use of deep structural reasoning and the addition of temporal reasoning capabilities. TEXSYS test results show the successful completion of both nominal control and fault recovery actions with the BATBS.
The Verification and Validation of a Magnetic Plasma Fluid Model Utilizing the MOOSE (Multiphysics Object Oriented Simulation Environment) Framework
As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification, benchmarking, and validation studies have been conducted. Verification studies involved utilizing the method of manufactured solutions and comparing the convergence slope of a known solution to the theoretical slope. Benchmarking consists of comparisons to existing edge codes, namely BOUT++ and SOLEDGE3X. Validation efforts focused on comparisons against open-source data from the TCV tokamak.
Effect of engine position and high-lift devices on aerodynamic characteristics of an external-flow jet-flap STOL model
Effect of engine position and high lift devices on aerodynamic characteristics of external flow, jet flap STOL model - graphs
Scalar Atomic Defect-Based Solid-State Self-calibrating Magnetometer (3SM) for Space Plasma Analysis
The Earth’s magnetosphere is a system of multiple, co-located particle populations interacting via plasma waves. Things to understand are driving processes, radiation belt and ring current issues, auroral physics, internal plasma processes, and magnetosphere-ionosphere mapping issues. These plasma-physics processes enable the Earth’s magnetosphere to evolve in response to temporal changes in the solar wind and they underlie the phenomena of space weather, which impacts spacecraft systems, astronauts, radio communications, and ground based electric-power grids. The objective of 3SM is to measure magnetic field strength and to calibrate the Vector Magnetometer (VM) device to maintain absolute accuracy during a mission. The 3SM features make the instrument preferably suited not only for the traditional role of scalar magnetometers as absolute references for the calibration of the on-board vector instruments, but also for extended operational capacities, such as higher frequency scalar measurements (of potential interest for magnetosphere studies for the low frequency part of the spectrum) or autonomous scalar / vector operations. Diamond has been the solid-state platform of choice for quantum device technologies for some time, however, it suffers from difficulties such as scalability, integration, and cost. While the diamond platform is very useful for quantum technologies, further development is needed to make it viable. The material platform of choice for NASA Glenn’s Quantum Sensing And Spin Physics (Q-SASP) is silicon carbide (SiC). This is due to the much higher industry development of the SiC material platform for high-power and high-temperature electronics. It leverages both the decades-long SiC development expertise and infrastructure at NASA Glenn and its growing capabilities in quantum metrology. To make SiC devices usable for quantum technologies such as quantum sources, a much deeper understanding of defects is needed. Q-SASP is developing quantum metrology capabilities to evaluate the energy structure, defect formation energy, band structure augmentation, generation/recombination rates, and limits of dipole-dipole coupling in non-metal implanted SiC devices. This can be achieved by analysis of zero-field splitting, low-field resonance, and singlet-triplet mixing through various forms of Electrically Detectable Magnetic Resonance (EDMR) and Near-Zero Field Magnetic Resonance (NZFMR) spectroscopy. This work will discuss recent system developments, device developments, computational modeling, and spectroscopy results and analysis of defects created by non-metal implantations in SiC devices. The defect formation energies of V Si ,V C , V C V Si , N C V Si , N Si , N C in 4H-SiC are previously reported values in other research [2]-[3]. The defect formation energies of PSi and PC were calculated in GPAW [fig 1A]. The basic underlying mechanism of the zero-field phenomenon is the mixing of singlet and triplet states [4]-[5]. In most spin-dependent transport, two electron spins are involved, and thus one must consider each of their interactions with the field. We investigated the electronic and magnetic properties of 4H-SiC and 6H-SiC. The defect formation energy helps us determine what types of defects we are observing in the SiC EDMR experiment. They have very low formation energy (it is negative). The phosphorus substitution in 4H-SiC is a very stable defect. The band diagrams provide us with vital information about how the electronic properties of SiC (such as band gap) change as we add non-metal defects. The zero-field splitting parameters allow us to study the inflection point in the NZFMR [fig 1B]. We clearly observed zero-field splitting. We also noted that the zero-field splitting remained constant with changing bias. We aspect it zero-field splitting to remain constant while the hyperfine and exchange interaction perturbations shift under the influence of an external magnetic field. This is the essence of quantum magnetometry and self-calibration.
A Review of Modeling Approaches for Understanding and Monitoring the Environmental Effects of Marine Renewable Energy
Understanding the environmental effects of marine energy (ME) devices is fundamental for their sustainable development and efficient regulation. However, measuring effects is difficult given the limited number of operational devices currently deployed. Numerical modeling is a powerful tool for estimating environmental effects and quantifying risks. It is most effective when informed by empirical data and coordinated with the development and implementation of monitoring protocols. We reviewed modeling techniques and information needs for six environmental stressor–receptor interactions related to ME: changes in oceanographic systems, underwater noise, electromagnetic fields (EMFs), changes in habitat, collision risk, and displacement of marine animals. This review considers the effects of tidal, wave, and ocean current energy converters. We summarized the availability and maturity of models for each stressor–receptor interaction and provide examples involving ME devices when available and analogous examples otherwise. Models for oceanographic systems and underwater noise were widely available and sometimes applied to ME, but need validation in real-world settings. Many methods are available for modeling habitat change and displacement of marine animals, but few examples related to ME exist. Models of collision risk and species response to EMFs are still in stages of theory development and need more observational data, particularly about species behavior near devices, to be effective. We conclude by synthesizing model status, commonalities between models, and overlapping monitoring needs that can be exploited to develop a coordinated and efficient set of protocols for predicting and monitoring the environmental effects of ME.
Electrodynamic Shaker Capability Estimation Through Experimental Dynamic Substructuring [Thesis]
Electrodynamic shaker systems are an essential tool in shock and vibration testing of dynamic environments. However, the specific performance capability of these systems is difficult to characterize. The dynamics of the shaker itself, the device under test and the specific test configuration used all couple to create a dynamic response unique to each test. Poorly predicted limitations in shaker capability affect the ability to achieve test specifications, delay testing schedules, and create difficulties for choosing test equipment. To predict shaker capability for a specific test configuration prior to setup, a lumped parameter model of the shaker system and a modal model of a device under test was developed. These models were then analytically coupled using LaGrange multiplier frequency based substructuring to estimate their coupled frequency response functions. The coupled frequency response functions were used to predict electrical inputs required to meet a given test specification. These input requirements were finally compared to a validation test using the specification and setup. Input requirements estimated using the substructuring estimated frequency response functions showed significant error. However, results using an ideal frequency response function showed very little error. These results indicate that with a better method of experimental dynamic substructuring employed it would be possible to accurately predict shaker capability for a given test configuration prior to setup.