Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Stochastic modelling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Learning-based demand-supply-coupled charging station location problem for electric vehicle demand management

We present a learning-based, demand-supply-coupled optimization model for the charging station location problem (CSLP), aiming to integrate the concept of electric vehicle (EV) charging demand management into the planning of charging infrastructures. In stage one, a gradient boosting-based learning model is developed to predict the charging demand of a charging station based on 15 defined features. Next, in stage two, a demand–supply-coupled CSLP model is developed to optimize the total charging usage rates of both existing and newly selected charging stations. We design a gradient-based stochastic spatial search algorithm to solve the proposed model. A case study with 6-year charging event data from Kansas City Missouri is performed. Results show that the proposed method can generate satisfactory charging demand predictions, and can increase charging usage rates by 14%, outperforming two benchmark approaches. Furthermore, the results of this research are poised to guide agencies in identifying optimal locations for new charging stations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Many-Exciton Quantum Dynamics in a Ruddlesden–Popper Tin Iodide

We present a study on the many-body exciton interactions in a Ruddlesden–Popper tin halide, namely, (PEA) 2 SnI 4 (PEA = phenylethylammonium), using coherent two-dimensional electronic spectroscopy. The optical dephasing times of the third-order polarization observed in these systems are determined by exciton many-body interactions and lattice fluctuations. We investigate the excitation-induced dephasing (EID) and observe a significant reduction of the dephasing time with increasing excitation density as compared to its lead counterpart (PEA) 2 PbI 4 , which we have previously reported in a separate publication [J. Chem. Phys. 2020, 153, 164706]. Surprisingly, we find that the EID interaction parameter is four orders of magnitude higher in (PEA) 2 SnI 4 than that in (PEA) 2 PbI 4 . This increase in the EID rate may be due to exciton localization arising from a more statically disordered lattice in the tin derivative. This is supported by the observation of multiple closely spaced exciton states and the broadening of the linewidth with increasing population time (spectral diffusion), which suggests a static disordered structure relative to the highly dynamic lead-halide. Additionally, we find that the exciton nonlinear coherent lineshape shows evidence of a biexcitonic state with low binding energy (<10 meV) not observed in the lead system. We model the lineshapes based on a stochastic scattering theory that accounts for the interaction with a nonstationary population of dark background excitations. Our study provides evidence of differences in the exciton quantum dynamics between tin- and lead-based Ruddlesden–Popper metal halides (RPMHs) and links them to the exciton–exciton interaction strength and the static disorder aspect of the crystalline structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Concurrent multi-peak Bragg coherent x-ray diffraction imaging of 3D nanocrystal lattice displacement via global optimization

Abstract In this paper we demonstrated a method to reconstruct vector-valued lattice distortion fields within nanoscale crystals by optimization of a forward model of multi-reflection Bragg coherent diffraction imaging (MR-BCDI) data. The method flexibly accounts for geometric factors that arise when making BCDI measurements, is amenable to efficient inversion with modern optimization toolkits, and allows for globally constraining a single image reconstruction to multiple Bragg peak measurements. This is enabled by a forward model that emulates the multiple Bragg peaks of a MR-BCDI experiment from a single estimate of the 3D crystal sample. We present this forward model, we implement it within the stochastic gradient descent optimization framework, and we demonstrate it with simulated and experimental data of nanocrystals with inhomogeneous internal lattice displacement. We find that utilizing a global optimization approach to MR-BCDI affords a reliable path to convergence of data which is otherwise challenging to reconstruct.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Stochastic 3D reconstruction of cracked polycrystalline NMC particles using 2D SEM data

Li-ion battery performance is strongly influenced by the 3D microstructure of its cathode particles. Cracks within these particles develop during calendaring and cycling, reducing connectivity but increasing reactive surface, making their impact on battery performance complex. Understanding these contradictory effects requires a quantitative link between particle morphology and battery performance. However, informative 3D imaging techniques are time-consuming, costly and rarely available, such that analyses often have to rely on 2D image data. This paper presents a novel stereological approach for generating virtual 3D cathode particles exhibiting crack networks that are statistically equivalent to those observed in 2D sections of experimentally measured particles. Consequently, 2D image data suffices for deriving a full 3D characterization of cracked cathodes particles. Such virtually generated 3D particles could serve as geometry input for spatially resolved electro-chemo-mechanical simulations to enhance our understanding of structure-property relationships of cathodes in Li-ion batteries.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Gravitational waves from primordial black hole evaporation with large extra dimensions

Abstract The spectra of gravitational waves from black hole evaporation generically peak at frequencies of order the Hawking temperature, making this signal ultra-high frequency for primordial black holes evaporating in the early universe. This motivates us to consider small black holes in theories with large extra dimensions, for which the peak frequency can be lowered substantially, since the true bulk Planck scaleM * can be much smaller than the effectiveM Pl . We study the emission of brane-localized gravitons during the Hawking evaporation of ultra-light primordial black holes in the context of theories with large extra dimensions, with the ultimate goal of computing the contribution to the stochastic gravitational wave background. To accurately model black hole evolution, we compute greybody factors for particles of spin-0, 1/2, 1, and 2 emitted on the brane and in the bulk, presuming the majority of emission proceeds during the Schwarzschild phase. We then compute the power spectrum and present day spectral density parameter for brane-localized gravitons contributing to a gravitational wave signal. We find that for an optimal choice of parameters, the peak frequency plateaus in the sub-MHz regime, within range of planned high-frequency gravitational wave detectors, making this scenario a target for detection once their sensitivity exceeds ΔN eff bounds.

Astronomy & Astrophysics↗
DOE OSTI2024

Stochastic Distribution Control Theory-Its Potential Application in Risk Management in Financial Systems

Stochastic Distribution Control (SDC) theory [1], originated by the author in 1996, aims at developing modeling and control strategies for dynamic and non-Gaussian stochastic systems by controlling the shape of the probability density functions of some concerned variables and parameters in stochastic systems. It generalizes the capability of standard stochastic differential equations and can therefore be applied to generic non-Gaussian systems. Since it was established in 1996, it has found a wide spectrum of applications in non-Gaussian stochastic system control, data mining, filtering and optimization for uncertain systems. In this short opinion article, discussions will be made on potential applications of SDC theory to financial systems in terms of risk analysis and management.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Potential Vorticity Mixing in a Tangled Magnetic Field

A theory of potential vorticity (PV) mixing in a disordered (tangled) magnetic field is introduced. The analysis is in the context of β -plane MHD, with a special focus on the physics of momentum transport in the stably stratified, quasi-2D solar tachocline. A physical picture of mean PV evolution by vorticity advection and tilting of magnetic fields is proposed. In the case of weak field perturbations, quasi-linear theory predicts that the Reynolds and magnetic stresses balance as turbulence Alfvénizes for a larger mean magnetic field. Jet formation is explored quantitatively in the mean field–resistivity parameter space. However, since even a modest mean magnetic field leads to large magnetic perturbations for large magnetic Reynolds number, the physically relevant case is that of a strong but disordered field. We show that numerical calculations indicate that the Reynolds stress is modified well before Alfvénization—i.e., before fluid and magnetic energies balance. To understand these trends, a double-average model of PV mixing in a stochastic magnetic field is developed. Calculations indicate that mean-square fields strongly modify Reynolds stress phase coherence and also induce a magnetic drag on zonal flows. The physics of transport reduction by tangled fields is elucidated and linked to the related quench of turbulent resistivity. We propose here a physical picture of the system as a resisto-elastic medium threaded by a tangled magnetic network. Applications of the theory to momentum transport in the tachocline and other systems are discussed in detail.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Control theory for random systems

A survey is presented of the current knowledge available for designing and predicting the effectiveness of controllers for dynamic systems which can be modeled by ordinary differential equations. A short discussion of feedback control is followed by a description of deterministic controller design and the concept of system state. The need for more realistic disturbance models led to the use of stochastic process concepts, in particular the Gauss-Markov process. A compensator controlled system, with random forcing functions, random errors in the measurements, and random initial conditions, is treated as constituting a Gauss-Markov random process; hence the mean-square behavior of the controlled system is readily predicted. As an example, a compensator is designed for a helicopter to maintain it in hover in a gusty wind over a point on the ground.

Bryson, A. E., Jr.↗
NASA NTRS1973

Suboptimal stochastic controller for an n-body spacecraft

The problem is studied of determining a stochastic optimal controller for an n-body spacecraft. The approach used in obtaining the stochastic controller involves the application, interpretation, and combination of advanced dynamical principles and the theoretical aspects of modern control theory. The stochastic controller obtained for a complicated model of a spacecraft uses sensor angular measurements associated with the base body to obtain smoothed estimates of the entire state vector, can be easily implemented, and enables system performance to be significantly improved.

Larson, V.↗
NASA NTRS1973

A guidance and navigation system for continuous low thrust vehicles

A midcourse guidance and navigation system for continuous low thrust vehicles is described. A set of orbit elements, known as the equinoctial elements, are selected as the state variables. The uncertainties are modelled statistically by random vector and stochastic processes. The motion of the vehicle and the measurements are described by nonlinear stochastic differential and difference equations respectively. A minimum time nominal trajectory is defined and the equation of motion and the measurement equation are linearized about this nominal trajectory. An exponential cost criterion is constructed and a linear feedback guidance law is derived to control the thrusting direction of the engine. Using this guidance law, the vehicle will fly in a trajectory neighboring the nominal trajectory. The extended Kalman filter is used for state estimation. Finally a short mission using this system is simulated. The results indicate that this system is very efficient for short missions.

Tse, C. J. C.↗
NASA NTRS1973

A guidance and navigation system for continuous low-thrust vehicles

A midcourse guidance and navigation system for continuous low thrust vehicles was developed. The equinoctial elements are the state variables. Uncertainties are modelled statistically by random vector and stochastic processes. The motion of the vehicle and the measurements are described by nonlinear stochastic differential and difference equations respectively. A minimum time trajectory is defined; equations of motion and measurements are linearized about this trajectory. An exponential cost criterion is constructed and a linear feedback quidance law is derived. An extended Kalman filter is used for state estimation. A short mission using this system is simulated. It is indicated that this system is efficient for short missions, but longer missions require accurate trajectory and ground based measurements.

Jack-Chingtse, C.↗
NASA NTRS1985

Composite Loads Spectra for Select Space Propulsion Structural Components: Probabilistic Load Model Development

This effort is in support of the development of the expert system of computer codes to predict the loads on select structural components of a space propulsion engine. The development will be based primarily on the space shuttle main engine (SSME) test data base. Because of random variations of the many different sources of the loadings on the selected structural components and transients, a probabilistic approach to the problems was adopted. The goal of this task is to characterize all of the individual sources of loads at critical structural locations, such as the turbine blades, the transfer ducts, and liquid oxygen posts, using state-of-the-art probabilistic methods with varying levels of sophistication. The second phase of this work is the development of a composite load model based on a probabilistic synthesis of the individual load model previously developed. This model will be based on the stochastic combination of the load variables and not on the physical process for the combination of the individual loads to the composite load seen by the selected structural components.

Kurth, R.↗
NASA NTRS1985

Cometary impacts, molecular clouds, and the motion of the sun perpendicular to the galactic plane

The stochastic nature of the mass extinction model of Rampino and Stothers (1984), based on the vertical oscillation of the solar system about the plane of the Galaxy, can accommodate a few events with large phase discrepancies. The degree of modulation is crucial in that it depends on the scale height of the population of molecular clouds relative to the amplitude of the solar system and tends to zero if this ratio is large and encounters are entirely random. Here data are presented here from CO surveys of molecular clouds both within and beyond the solar circle which permit explicit calculation of the strength of the modulation. The cloud layer near the sun it too extended and, as a consequence, the modulation of cloud encounters is too weak for a statistically significant period to be extracted from the nine extinctions analyzed by Rampino and Stothers.

Thaddeus, P.↗
NASA NTRS1990

Performance evaluation of a Doppler radar system for wind shear detection

Nonlinear stochastic differential equations are used to model wind shear, and extended Kalman filters are used to generate state estimates from measurements received from a Doppler radar onboard an aircraft. Likelihood-ratio tests are then used to detect the presence of wind shear. The performance of the system is evaluated by deriving theoretical expressions for the false alarm and miss error probabiilties. The approach uses a Fokker-Planck equation. The overall methodology is general and should be of interest in other applications.

Khalaf, Camille S.↗
NASA NTRS1993

Bifurcation analysis of a simple analytic model of self-propagating star formation

We investigate the structure and stability of rotationally symmetric nonhomogeneous time-independent solutions derived from a simple analytic model of self-propagating star formation. For this purpose we employ two methodologies: We use bifurcation theoretical methods to prove the existence of nonhomogeneous axisymmetric stationary solutions of an appropriate nonlinear evolution equation for the stellar density. We show that the nonhomogeneous solution branch bifurcates from the homogeneous one at a critical parameter value of the star formation rate. Further, the analytical theory allows us to show that the new solution set is stable in the weakly nonlinear regime near the bifurcation point. To follow the solution branch further, we use numerical methods. The numerical calculation shows the structure and stability of these solutions. We conclude that no periodic time-dependent solutions of this special model exist, and no further bifurcations can be found. The same results have been found in simulations of stochastic self-propagating star formation based on similar models. Therefore, our findings provide a natural explanation, why long-lived large-scale structure have not been found in those simulations.

Neukirch, Thomas↗
NASA NTRS2002

Health Monitoring for Airframe Structural Characterization

This study established requirements for structural health monitoring systems, identified and characterized a prototype structural sensor system, developed sensor interpretation algorithms, and demonstrated the sensor systems on operationally realistic test articles. Fiber-optic corrosion sensors (i.e., moisture and metal ion sensors) and low-cycle fatigue sensors (i.e., strain and acoustic emission sensors) were evaluated to validate their suitability for monitoring aging degradation; characterize the sensor performance in aircraft environments; and demonstrate placement processes and multiplexing schemes. In addition, a unique micromachined multimeasure and sensor concept was developed and demonstrated. The results show that structural degradation of aircraft materials could be effectively detected and characterized using available and emerging sensors. A key component of the structural health monitoring capability is the ability to interpret the information provided by sensor system in order to characterize the structural condition. Novel deterministic and stochastic fatigue damage development and growth models were developed for this program. These models enable real time characterization and assessment of structural fatigue damage.

Munns, Thomas E.↗
NASA NTRS2007

A Black-Scholes Approach to Satisfying the Demand in a Failure-Prone Manufacturing System

The goal of this paper is to use a financial model and a hedging strategy in a systems application. In particular, the classical Black-Scholes model, which was developed in 1973 to find the fair price of a financial contract, is adapted to satisfy an uncertain demand in a manufacturing system when one of two production machines is unreliable. This financial model together with a hedging strategy are used to develop a closed formula for the production strategies of each machine. The strategy guarantees that the uncertain demand will be met in probability at the final time of the production process. It is assumed that the production efficiency of the unreliable machine can be modeled as a continuous-time stochastic process. Two simple examples illustrate the result.

Chavez-Fuentes, Jorge R.↗
NASA NTRS2008

The Mock LISA Data Challenge Round 3: New and Improved Sources

The Mock LISA Data Challenges are a program to demonstrate and encourage the development of data-analysis capabilities for LISA. Each round of challenges consists of several data sets containing simulated instrument noise and gravitational waves from sources of undisclosed parameters. Participants are asked to analyze the data sets and report the maximum information they can infer about the source parameters. The challenges are being released in rounds of increasing complexity and realism. Challenge 3. currently in progress, brings new source classes, now including cosmic-string cusps and primordial stochastic backgrounds, and more realistic signal models for supermassive black-hole inspirals and galactic double white dwarf binaries.

Baker, John↗