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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 307 records · Page 17

Probability of failure and risk assessment of propulsion structural components

The probabilistic structural analysis method (PSAM) was developed to analyze the effects of fluctuating loads, variable material properties, and uncertain analytical models especially for high performance structures such as the Space Shuttle Main Engine turbopump blades. Risk is calculated after expensive service experience. However, probabilistic structural analysis provides a rational alternative method to quantify uncertainties in the structural performance and durability. NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a probabilistic structural analysis computer code which integrates finite element methods and reliability algorithms, capable to predicting the probability distributions of structural response variables such as stress, displacement, natural frequencies, and buckling loads. This computer code is detailed.

Shiao, Michael C.↗

Stochastic Optimal Control via Bellman's Principle

This paper presents a method for finding optimal controls of nonlinear systems subject to random excitations. The method is capable to generate global control solutions when state and control constraints are present. The solution is global in the sense that controls for all initial conditions in a region of the state space are obtained. The approach is based on Bellman's Principle of optimality, the Gaussian closure and the Short-time Gaussian approximation. Examples include a system with a state-dependent diffusion term, a system in which the infinite hierarchy of moment equations cannot be analytically closed, and an impact system with a elastic boundary. The uncontrolled and controlled dynamics are studied by creating a Markov chain with a control dependent transition probability matrix via the Generalized Cell Mapping method. In this fashion, both the transient and stationary controlled responses are evaluated. The results show excellent control performances.

Crespo, Luis G.↗

Improving Sensorimotor Function Using Stochastic Vestibular Stimulation

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transition phases. Post flight sensorimotor changes may include postural and gait instability, spatial disorientation, and visual performance decrements, all of which can degrade operational capabilities of the astronauts and endanger the crew. Crewmember safety would be improved if these detrimental effects of spaceflight could be mitigated by a sensorimotor countermeasure and even further if adaptation to baseline could be facilitated. The goal of this research is to investigate the potential use of stochastic vestibular stimulation (SVS) as a technology to improve sensorimotor function. We hypothesize that low levels of SVS will improve sensorimotor performance through stochastic resonance (SR). The SR phenomenon occurs when the response of a nonlinear system to a weak input signal is optimized by the application of a particular nonzero level of noise. Two studies have been initiated to investigate the beneficial effects and potential practical usage of SVS. In both studies, electrical vestibular stimulation is applied via electrodes on the mastoid processes using a constant current stimulator. The first study aims to determine the repeatability of the effect of vestibular stimulation on sensorimotor performance and perception in order to better understand the practical use of SVS. The beneficial effect of low levels of SVS on balance performance has been shown in the past. This research uses the same balance task repeated multiple times within a day and across days to study the repeatability of the stimulation effects. The balance test consists of 50 sec trials in which the subject stands with his or her feet together, arms crossed, and eyes closed on compliant foam. Varying levels of SVS, ranging from 0-700 micro A, are applied across different trials. The subject-specific optimal SVS level is that which results in the best balance performance as measured by inertial measurement units placed on the upper and lower torso of the subjects. Additionally, each individual’s threshold for illusory motion perception of suprasensory electrical vestibular stimulation is measured multiple times within and across days to better understand how multiple SVS test methods compare. The second study aims to demonstrate stochastic resonance in the vestibular system using a perception based motion recognition task. This task measures an individual’s velocity threshold of motion recognition using a 6-degree of freedom Stewart platform and a 3-down/1-up staircase procedure. For this study, thresholds are determined using 150 trials in the upright, head-centered roll tilt motion direction at a 0.2 Hz frequency. We aim to demonstrate the characteristic bell shaped curve associated with stochastic resonance with each subject’s motion recognition thresholds at varying SVS levels ranging from 0 to 1500 micro A. The curve includes the individual’s baseline threshold with no SVS, optimal or minimal threshold at some mid-level of SVS, and finally degraded or increased threshold at a high SVS level. An additional aim is to formally retest each subject at his or her individual optimal SVS level on a different day than the original testing for additional validity. The overall purpose of this research is to further quantify the effects of SVS on various sensorimotor tasks and investigate the practical implications of its use in the context of human space flight so that it may be implemented in the future as a component of a comprehensive countermeasure plan for adaptation to G-transitions.

Galvan, R. C.↗

Optimal Control of Differentially Private EV Charging: A Scalable Learning Approach Under Uncertainty

Internet of Things (IoT)-enabled electric vehicles (IoEVs) enable intelligent charging coordination that accounts for grid congestion. However, increased data exchange raises privacy concerns, as charging patterns can reveal sensitive driver behavior to grid operators. Here, we propose a differentially private (DP) EV charging framework that enables coordinated control while protecting driver data with theoretical privacy guarantees. Nevertheless, integrating DP inevitably introduces uncertainty into the control strategy for EVs, which can lead to infeasible solutions. To tackle this challenge, we develop a feasible and scalable control algorithm based on constrained reinforcement learning (CRL) and convex hulls. While our framework is designed to handle the uncertainty introduced by DP, it is general and also applicable to other sources of uncertainty in EV charging, such as the stochastic nature of driver behavior and renewable variability. This ensures feasible and privacy-preserving coordination of EV charging at scale. Our method constructs convex hulls within the action space to guarantee feasibility under stochastic constraints and incorporates constraint reduction techniques to improve scalability. Case studies based on IEEE benchmark systems demonstrate that the proposed approach effectively balances feasibility under uncertainty, scalability, and privacy in large-scale EV charging control.

Engineering - Power transmission and distribution↗

A DSMC Surface Chemistry Model for Carbon-Based Ablators

A detailed molecular surface chemistry model for the DSMC (Direct Simulation Monte Carlo) method is proposed and implemented into the SPARTA (Stochastic PArallel Rarefied-gas Time-accurate Analyzer) DSMC solver. Molchanova et al. constructed a molecular model for surface recombination in DSMC that includes different surface processes (adsorption, desoprtion, Eley-Rideal and Langmuir-Hinshelwood). All surface processes can be divided into two groups: surface mechanisms, which involve only the particle adsorbed by the surface (desorption and Langmuir-Hinshelwood), and impact mechanisms, which also involve gas-phase particles (adsorption, Eley-Rideal). Using a similar approach, the 14-reaction kinetic model of oxygen-carbon interaction suggested by Zhlukhtov and Abe, as well as more recent models by Alba et al., Poovathinghal et al., and a new model developed in the scope of this work, are implemented in SPARTA. The computational results for the different oxidation models are compared with experimental results from Murray et al. (oxidation of a vitreous carbon surface due to a hyperthermal beam of O and O2), with a particular focus on fluxes, angular and Time-Of-Flight distributions of scattered particles.

oxidation↗

A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions

Neural network wavefunctions optimized using the variational Monte Carlo method have been shown to produce highly accurate results for the electronic structure of atoms and small molecules, but the high cost of optimizing such wavefunctions prevents their application to larger systems. We propose the Subsampled Projected-Increment Natural Gradient Descent (SPRING) optimizer to reduce this bottleneck. SPRING combines ideas from the recently introduced minimum-step stochastic reconfiguration optimizer (MinSR) and the classical randomized Kaczmarz method for solving linear least-squares problems. We demonstrate that SPRING outperforms both MinSR and the popular Kronecker-Factored Approximate Curvature method (KFAC) across a number of small atoms and molecules, given that the learning rates of all methods are optimally tuned. For example, on the oxygen atom, SPRING attains chemical accuracy after forty thousand training iterations, whereas both MinSR and KFAC fail to do so even after one hundred thousand iterations.

97 MATHEMATICS AND COMPUTING↗

Scatter in Carbon/Silicon Carbide (C/SiC) Composites Quantified

Carbon-fiber-reinforced silicon carbide matrix (C/SiC) composites processed by chemical vapor infiltration are candidate materials for aerospace thermal structures. Carbon fibers can retain properties at very high temperatures, but they are known to have poor oxidation resistance in adverse, high-temperature environments. Nevertheless, the combination of CVI-SiC matrix with higher stiffness and oxidation resistance, the interfacial coating, and additional surface-seal coating provides the necessary protection to the carbon fibers, and makes the material viable for high-temperature space applications operating under harsh environments. Furthermore, C/SiC composites, like other ceramic matrix composites (CMCs), exhibit graceful non-catastrophic failure because of various inherent energy dissipating mechanisms. The material exhibits nonlinearity in deformation even at very low stress levels. This is the result of the severe matrix microcracking present in the as processed composite because of large differences between the coefficients of thermal expansion of the fiber and the matrix. Utilization of these advanced composites in next generation space vehicles will require innovative structural configurations, updated materials, and refined analyses. Structural safety issues for these vehicles are in direct competition with performance and cost. One would have to quantify the uncertainties associated with the design using formal probabilistic methods. Specifically four fundamental aspects on which analyses are based-- (1) loading conditions, (2) material behavior, (3) geometrical configurations, and (4) structural connections between the composite components and baseline structure--are stochastic in nature. A direct way to formally account for uncertainties is to develop probabilistic structural analysis methods where all participating variables are described by appropriate probability density functions. The present work, however, focuses on analyzing the stochastic material behavior of these advanced composites using formal probabilistic analysis methods. Often, some of the desirable property characteristics that allow composites to offer advantages over conventional structural materials (like tailoring of composite properties) and the complexity are in fact responsible for their greater statistical variability and the requirements for more characterization tests. Composite properties are anisotropic as well, having different properties in different directions. This means that characterization of a property such as stiffness--which will vary greatly depending on the orientation of the fiber relative to the direction of the testing--must be repeated for several different directions and loading conditions. The fabrication process for composites also introduces statistical variations in properties and geometry. A composite part is produced in a number of steps, each of which introduces statistical variability. The matrix is usually produced from a combination of raw materials; and the fiber, which has its own set of properties, is often coated or surface treated, introducing yet another source of variability.

Murthy, Pappu L. N.↗

A survey of design methods for failure detection in dynamic systems

A number of methods for the detection of abrupt changes (such as failures) in stochastic dynamical systems were surveyed. The class of linear systems were emphasized, but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed.

Willsky, A. S.↗

Non-local transport in radiation-hydrodynamics codes for ICF by efficient coupling to an external Vlasov–Fokker–Planck code

Accurately incorporating non-local transport into radiation-hydrodynamics codes, and indeed any fluid system, has long been elusive. To date, a simplified and accurate theory that can be easily integrated has not been available. This limitation affects modeling in inertial confinement fusion (ICF) and magnetic confinement fusion systems, among others, where non-local transport is well-known to be present. Here, we present a coupling methodology between a full Vlasov–Fokker–Planck (VFP) electron kinetic code and radiation-hydrodynamics (rad-hydro) codes. The VFP code is used to adjust native electron transport in the rad-hydro code, thus enabling improved transport without the need to integrate a full electron VFP solver into the rad-hydro code. This approach necessitates only occasional invocation of the VFP code, reducing computational intensity compared to following the dynamic evolution entirely with the VFP code on fluid time scales. We illustrate that the methodology is more accurate than other simplified methods in thermal decay systems relevant to ICF and can replicate standard theoretical results with high accuracy.

Electronic transport↗

Control optimization, stabilization and computer algorithms for aircraft applications

Computationally useful algorithms are considered that can aid the control engineer in designing systems control in linear time invariant dynamics for aircraft applications. Structural aspects of system identification, matrix parameterization, and the effect of feedback on identifiability of systems. Adaptive and stochastic control model constructions are projected, and a method for approximate identification of aircraft characteristics and subsequent generation of control signals is outlined.

Mitter, S. K.↗

Approximations to and local properties of diffusions with discontinuous controls

The paper discusses several properties of control systems defined by stochastic differential equations, which are defined by the method of Girsanov, using a transformation of measures, and where the controls are discontinuous. Uniqueness of the multivariate distributions of the process is proved, and it is shown that the process is a limit, in a natural sense, of a certain discrete time approximation. Other questions, concerning the effects on the distributions of the paths, and of the cost of approximating the control by a smooth control and concerning local properties of the solution, are discussed.

Kushner, H. J.↗

Analysis of bilinear stochastic systems

Analysis of stochastic dynamical systems that involve multiplicative (bilinear) noise processes is considered. After defining the systems of interest, the evolution of the moments of such systems, the question of stochastic stability, and estimation for bilinear stochastic systems are discussed. Both exact and approximate methods of analysis are introduced, and, in particular, the uses of Lie-theoretic concepts and harmonic analysis are discussed.

Willsky, A. S.↗

Integrator Windup Protection-Techniques and a STOVL Aircraft Engine Controller Application

Integrators are included in the feedback loop of a control system to eliminate the steady state errors in the commanded variables. The integrator windup problem arises if the control actuators encounter operational limits before the steady state errors are driven to zero by the integrator. The typical effects of windup are large system oscillations, high steady state error, and a delayed system response following the windup. In this study, methods to prevent the integrator windup are examined to provide Integrator Windup Protection (IW) for an engine controller of a Short Take-Off and Vertical Landing (STOVL) aircraft. An unified performance index is defined to optimize the performance of the Conventional Anti-Windup (CAW) and the Modified Anti-Windup (MAW) methods. A modified Genetic Algorithm search procedure with stochastic parameter encoding is implemented to obtain the optimal parameters of the CAW scheme. The advantages and drawbacks of the CAW and MAW techniques are discussed and recommendations are made for the choice of the IWP scheme, given some characteristics of the system.

KrishnaKumar, K.↗

Probabilistic Structural Analysis Theory Development

The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.

Burnside, O. H.↗

A Vibrational Energy Harvesting Sensor Based on Linear and Rotational Electromechanical Effects

In this investigation, a magnetically coupled double-spring design is presented for harvesting low-level non-stationary random vibrational energy. The sensor relies on multimodal coupling between the translation and rotation of a two-spring magnet and coil system to widen the harvesting bandwidth. Energy methods are used to develop a model to characterize the electromechanical response of the system, the solution of which is obtained using stochastic techniques based on a particle swarm algorithm. This approach provides an efficient method to estimate system parameters that otherwise are difficult or impossible to determine with independent measurements. The experimental results demonstrate agreement with the theoretical predictions over a limited bandwidth. The sensor can effectively harvest non-stationary vibration energy down to 10 -4 g within a limited bandwidth of 130–150 Hz. The sensor prototype has an operational volume of 2.6 cm 3 with a calculated power density of 0.2 W/cm 3 . The sensor’s small size results in a coupling efficiency of approximately 6% across the tested bandwidth.

42 ENGINEERING↗

Tuning Monotonic Basin Hopping: Improving the Efficiency of Stochastic Search as Applied to Low-Thrust Trajectory Optimization

Trajectory optimization methods using MBH have become well developed during the past decade. An essential component of MBH is a controlled random search through the multi-dimensional space of possible solutions. Historically, the randomness has been generated by drawing RVs from a uniform probability distribution. Here, we investigate the generating the randomness by drawing the RVs from Cauchy and Pareto distributions, chosen because of their characteristic long tails. We demonstrate that using Cauchy distributions (as first suggested by Englander significantly improves MBH performance, and that Pareto distributions provide even greater improvements. Improved performance is defined in terms of efficiency and robustness, where efficiency is finding better solutions in less time, and robustness is efficiency that is undiminished by (a) the boundary conditions and internal constraints of the optimization problem being solved, and (b) by variations in the parameters of the probability distribution. Robustness is important for achieving performance improvements that are not problem specific. In this work we show that the performance improvements are the result of how these long-tailed distributions enable MBH to search the solution space faster and more thoroughly. In developing this explanation, we use the concepts of sub-diffusive, normally-diffusive, and super-diffusive RWs originally developed in the field of statistical physics.

mission design↗