Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sequential analysis”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Theory of x-ray photon correlation spectroscopy for multiscale flows

Complex multiscale flows associated with instabilities and turbulence are commonly induced under high-energy density (HED) conditions, but accurate measurement of their transport properties has been challenging. X-ray photon correlation spectroscopy (XPCS) with coherent x-ray sources can, in principle, probe material dynamics to infer transport properties using time autocorrelation of density fluctuations. Here we develop a theoretical framework for utilizing XPCS to study material diffusivity in multiscale flows. We extend single-scale shear flow theories to broadband flows using a multiscale analysis that captures shear and diffusion dynamics. Our theory is validated with simulated XPCS for Brownian particles advected in multiscale flows. We demonstrate the versatility of the method over several orders of magnitude in timescale using sequential-pulse XPCS, single-pulse x-ray speckle visibility spectroscopy (XSVS), and double-pulse XSVS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1972

Multistage, multiband and sequential imagery to identify and quantify non-forest vegetation resources

Earth Resources photographs from Apollo 6, 7, and 9 and photographs taken during Gemini 4, were used in the research along with high altitude and conventional aerial photography. A unified land use and resource analysis system was devised and used to develop a mapping legend. The natural vegetation, land use, macrorelief, and landforms of northern Maricopa County, Arizona, were analyzed and inventoried. This inventory was interpreted in relation to the critical problem of urban expansion and agricultural production in the study area. The central thrust of the research program has been to develop methods for use of space and small-scale, high-altitude aerial photography to develop information for land use planning and resource allocation decisions.

Driscoll, R. S.↗
NASA NTRS2007

Finite Element Simulation of Solid Rocket Booster Separation Motors During Motor Firing

One of the toughest challenges facing Solid Rocket Booster (SRB) engineers is to ensure that any design changes made to the Shuttle-Derived Booster Separation Motors (BSM) for future space exploration vehicles is able to withstand the increasingly hostile motor firing environment without cracking its critical component - the graphite throat. This paper presents a critical analysis methodology and techniques for assessing effects of BSM design changes with great accuracy and precision. For current Space Shuttle operation, the motor firing occurs at SRB separation - approximately 125 seconds after Shuttle launch at an altitude of about 28 miles. The motor operation event lasts about two seconds, however, the surface temperature of the graphite throat increases approximately 3400 F in less than one second with a corresponding increase in surface pressure of approximately 2200 pounds per square inch (psi) in less than one-tenth of a second. To capture this process fully and accurately, a two-phase sequentially coupled thermal-mechanical finite element approach was developed. This method allows the time- and location-dependent pressure fields to interact with the spatial-temporal thermal fields throughout the operation. The material properties of graphite throat are orthotropic and temperature-dependent. The analysis involves preload and multiple body contacts.

Yu. Weiping↗
DOE OSTI2025

Parallelizing autotuning for HPC applications: Unveiling the potential of the speculation strategy in Bayesian optimization

In the exascale computing era, tuning High-Performance Computing (HPC) applications has become a significant computational challenge. Although Bayesian optimization (BO) has emerged as a promising tool for HPC performance tuning, the BO workflow is inherently sequential (i.e., one function evaluation at a time) and cannot leverage the huge amount of parallel resources present in modern supercomputers, resulting in a considerable underutilization of their computational capabilities. This paper explores the trade-off between search quality and parallelism in BO, investigating a diverse set of methods. Building upon both previous approaches from the literature and novel methodologies introduced in this work, our study provides a deep analysis to accelerate BO performance tuning. By examining a set of synthetic functions and practical HPC applications, our exploration analyzes the interaction among various BO methods for parallelization, the quantity of parallel resources, the runtime distribution of target HPC applications, and the costs associated with different search orchestration mechanisms that have been overlooked in previous studies. Compared to sequential BO, our novel methodology achieves comparable quality while demonstrating robust scalability in search time as the amount of parallel resources increases; it also outperforms a state-of-the-art tuner, which supports parallelization, achieving up to 3.67x faster search time. We provide high-value insights for practitioners seeking to leverage the power of parallel computing for efficient HPC application tuning. Additionally, to further assist researchers in accelerating the performance tuning of their HPC applications, we provide an extension of an existing open-source tuning framework that incorporates our methods.

Bayesian optimization↗
DOE OSTI2024

Automated Bayesian high-throughput estimation of plasma temperature and density from emission spectroscopy

Here, this paper introduces a novel approach for automated high-throughput estimation of plasma temperature and density using atomic emission spectroscopy, integrating Bayesian inference with sophisticated physical models. We provide an in-depth examination of Bayesian methods applied to the complexities of plasma diagnostics, supported by a robust framework of physical and measurement models. Our methodology is demonstrated using experimental observations in the field of magneto-inertial fusion, focusing on individual and sequential shot analyses of the Plasma Liner Experiment at LANL. The results demonstrate the effectiveness of our approach in enhancing the accuracy and reliability of plasma parameter estimation and in using the analysis to reveal the deep hidden structure in the data. This study not only offers a new perspective of plasma analysis but also paves the way for further research and applications in nuclear instrumentation and related domains.

Bayesian inference↗
NASA NTRS1985

Future possibilities in objective analysis and data assimilation for atmospheric dynamics

The role that dynamics plays in estimating the state of the atmosphere from incomplete and noisy data is reviewed. Objective analysis represents an attempt at relying mostly on the data and minimizing the role of dynamics in the estimation. Data assimilation tries to balance properly the roles of dynamical and observational information. Sequential estimation is presented as the proper framework for understanding this balance, and the Kalman filter as the ideal, optimal procedure for data assimilation. The optimal filter computes forecast error covariances of a given atmospheric model exactly, and hence data assimilation should be closely connected with predictability studies. This connection is described, and consequences drawn for currently active areas of the atmospheric and related sciences, namely, mesoscale meteorology, long range forecasting, and upper ocean dynamics. Possibilities offered by judicious data assimilation in understanding barotropic adjustment, a phenomenon that appears to play a crucial role in atmospheric behavior on the scale of weeks to months, and hence in long range forecasting are addressed.

Ghil, M.↗
NASA NTRS2012

Algorithm for Compressing Time-Series Data

An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

Hawkins, S. Edward, III↗
NASA NTRS1993

Determination of atomic oxygen fluence using spectrophotometric analysis of infrared transparent witness coupons for long duration exposure tests

Atomic oxygen degradation is one of several major threats to the durability of spaceborne systems in low Earth orbit. Ground-based simulations are conducted to learn how to minimize the adverse effects of atomic oxygen exposure. Assessing the fluence of atomic oxygen in test chambers such as a plasma asher over long periods of time is necessary for accurate determination of atomic oxygen exposure. Currently, an atomic oxygen susceptible organic material such as Kapton is placed next to samples as a witness coupon and its mass loss is monitored and used to determine the effective atomic oxygen fluence. However, degradation of the Kapton witness coupons occurs so rapidly in plasma ashers that for any long term test many witness coupons must be used sequentially in order to keep track of the fluence. This necessitates opening vacuum to substitute fresh coupons. A passive dosimetry technique was sought to monitor atomic oxygen exposure over longer periods without the need to open the plasma asher to the atmosphere. This paper investigates the use of spectrophotometric analysis of durable IR transparent witness coupons to measure atomic oxygen exposure for longer duration testing. The method considered would be conductive to making in situ measurements of atomic oxygen fluence.

Podojil, Gregg M.↗
NASA NTRS1980

Numerical calculation of transonic axial turbomachinery flows

This paper presents a numerical method and the results of a computer program for solving an exact, three-dimensional, full-potential equation that models rotating and nonrotating inviscid, absolutely irrotational, homentropic flows. Besides calculating the flows through an arbitrarily shaped rotor or stator blade row mounted on an axisymmetric hub and confined in an axisymmetric duct, the computer program is also capable of analysing flow fields about arbitrarily shaped wing-body combinations, propellers, helicopter rotors in hover, and wind turbine rotors. The governing equation is solved numerically in a fully conservative form by using an artificial time concept, a finite volume technique, rotated type-dependent differencing, successive line overrelaxation, and sequential boundary-conforming grid refinement. An artificial viscosity is added in fully conservative form; and an initial guess for the potential field is applied, as determined by a two-dimensional cascade analysis.

Dulikravich, D. S.↗
NASA NTRSDate not supplied

Changes in Plants Developed from Imbibed Seeds Irradiated by Simulated Solar Particle Events

One of the major concerns for long-term exploration missions beyond the Earth’s magnetosphere is radiation risk primarily from solar particle events (SPEs) and galactic cosmic rays (GCRs). With the goal of enabling manned Mars exploration, the production of fresh food during long duration space missions may provide nutritional supplementation and benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. In this study, we evaluated the effect of simulated SPEs on imbibed seeds of mizuna mustard, ‘Outredgeous’ red romaine lettuce, and ‘Red Robin’ dwarf tomato. Seeds were exposed to various doses of simulated SPEs (0, 40, 80 cGy, and 200 cGy), either acutely or at a low dose rate (LDR only for 40 and 80 cGy doses), using the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). Simulated SPE exposure was achieved using sequential exposures to protons with a broad energy range at 50-150 MeV/n. Control and irradiated seeds were planted either onto 0.5% MS-based agar plates containing required nutrients for early seedling analysis, or in peat plugs/pots for 28 day (mizuna and lettuce) and 91 day (tomato) grow outs. All plants were maintained under space-vehicle relevant conditions at 3000 ppm CO2, 50% RH, and 23°C, and a 16/8 h photoperiod with 300 μmol·m(exp -2)·s(exp -1) photosynthetically active radiation. Plant/fruit morphometrics and edible fresh mass were measured. Additionally, nutrient analyses were performed on mizuna and tomato fruit. Seedlings from irradiated seeds (both 40 and 80 cGy) showed significant and dose dependent impacts on cotyledon development and root length. Interestingly, small, but significant changes in vitamin content were found in mizuna and tomato fruits grown from 80 cGy (LDR) irradiated seeds. In addition, 80 cGy (LDR) simulated SPEs significantly delayed tomato early seedling development and plant growth, and reduced the quantity of fruits produced from the surviving plants. (This study was supported by NASA Human Research Program.)

J. T. Richards↗
NASA NTRSDate not supplied

Changes in Plants Developed from Imbibed Seeds Irradiated by Simulated Solar Particle Events

One of the major concerns for long-term exploration missions beyond the Earth’s magnetosphere is radiation risk primarily from solar particle events (SPEs) and galactic cosmic rays (GCRs). With the goal of manned Mars exploration, the production of fresh food during long duration space missions may provide nutritional supplementation and benefit astronauts’ behavioral health. However, the effects of space radiation on plants and plant propagules have not been sufficiently investigated and characterized. In this study, we evaluated the effect of simulated SPEs on imbibed seeds of mizuna mustard, ‘Outredgeous’ red romaine lettuce, and ‘Red Robin’ dwarf tomato. Seeds were exposed to various doses of simulated SPEs (0, 40, 80 cGy, and 200 cGy), either acutely or at a low dose rate (LDR only for 40 and 80 cGy doses), using the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). Simulated SPE exposure was achieved using sequential exposures to protons with a broad energy range at 50-150 MeV/n. Control and irradiated seeds were planted either onto 0.5% MS-based agar plates containing required nutrients for early seedling analysis, or in peat plugs/pots for 28 day (mizuna and lettuce) and 91 day (tomato) grow outs. All plants were maintained under space-vehicle relevant controlled environment conditions at 3000 ppm CO2, 50% RH, and 23°C, and a 16/8 h photoperiod with 300 μmol·m-2·s-1 photosynthetically active radiation. Plant/fruit morphometrics and edible fresh mass were measured. In addition, nutrient analyses were performed for both mizuna and ripe tomatoe fruit. Seedlings from irradiated seeds (both 40 cGy and 80 cGy) showed significant changes in cotyledon development, as well as root length. Interestingly, small, but significant changes in vitamin content were found in mizuna and tomato fruits grown from 80 cGy (LDR) irradiated seeds. In addition, 80 cGy (LDR) simulated SPEs significantly affected tomato early seedling development, plant growth, and the quantity of fruits produced from the surviving plants. Generally, compared to 80 cGy, 40 cGy (LDR) of simulated SPEs displayed some impacts to the seeds and seedlings, but to a much lesser degree. (This study was supported by NASA Human Research Program.)

J.T. Richards↗
NASA NTRS2012

A Risk-Constrained Multi-Stage Decision Making Approach to the Architectural Analysis of Mars Missions

This paper presents a novel risk-constrained multi-stage decision making approach to the architectural analysis of planetary rover missions. In particular, focusing on a 2018 Mars rover concept, which was considered as part of a potential Mars Sample Return campaign, we model the entry, descent, and landing (EDL) phase and the rover traverse phase as four sequential decision-making stages. The problem is to find a sequence of divert and driving maneuvers so that the rover drive is minimized and the probability of a mission failure (e.g., due to a failed landing) is below a user specified bound. By solving this problem for several different values of the model parameters (e.g., divert authority), this approach enables rigorous, accurate and systematic trade-offs for the EDL system vs. the mobility system, and, more in general, cross-domain trade-offs for the different phases of a space mission. The overall optimization problem can be seen as a chance-constrained dynamic programming problem, with the additional complexity that 1) in some stages the disturbances do not have any probabilistic characterization, and 2) the state space is extremely large (i.e, hundreds of millions of states for trade-offs with high-resolution Martian maps). To this purpose, we solve the problem by performing an unconventional combination of average and minimax cost analysis and by leveraging high efficient computation tools from the image processing community. Preliminary trade-off results are presented.

entry, descent, and landing (EDL)↗
NASA NTRS2024

Envisioning an Optimal Network of Space-Based Lasers for Orbital Debris Remediation

The rapid increase in resident space objects, including satellites and orbital debris, poses a significant threat to the safety and sustainability of space missions. This paper explores orbital debris remediation using a network of collaborative space-based lasers, leveraging laser ablation for momentum transfer on debris. A novel delta-v vector analysis framework quantifies the e↵ects of multiple simultaneous laser-to-debris (L2D) engagements by using vector composition of the imparted delta-v vectors. The paper introduces the Concurrent LocationScheduling Problem (CLSP), which optimizes the placement of laser platforms and the scheduling of L2D engagements to maximize debris remediation capacity. Due to the computational complexity of the CLSP, it is decomposed into two sequential subproblems: (1) optimal laser platform locations are determined using the Maximal Covering Location Problem, and (2) a novel integer linear programming-based approach schedules L2D engagements within the network configuration to maximize remediation capacity. Computational experiments are conducted to evaluate the proposed framework’s e↵ectiveness under various mission scenarios, demonstrating key network functions such as collaborative nudging, deorbiting, and just-in-time collision avoidance. A sensitivity analysis further examines how varying the number and distribution of laser platforms a↵ects debris remediation capacity, providing insights into optimizing the performance of space-based laser networks.

David O Williams Rogers↗
NASA NTRS2012

A Bayesian Framework for Reliability Analysis of Spacecraft Deployments

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a two stage sequential Bayesian framework for reliability estimation of spacecraft deployment was developed for this purpose. This process was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the Optical Telescope Element. Initially, detailed studies of NASA deployment history, "heritage information", were conducted, extending over 45 years of spacecraft launches. This information was then coupled to a non-informative prior and a binomial likelihood function to create a posterior distribution for deployments of various subsystems uSing Monte Carlo Markov Chain sampling. Select distributions were then coupled to a subsequent analysis, using test data and anomaly occurrences on successive ground test deployments of scale model test articles of JWST hardware, to update the NASA heritage data. This allowed for a realistic prediction for the reliability of the complex Sunshield deployment, with credibility limits, within this two stage Bayesian framework.

Evans, John W.↗
NASA NTRS1998

In-Flight System Identification

A method is proposed and studied whereby the system identification cycle consisting of experiment design and data analysis can be repeatedly implemented aboard a test aircraft in real time. This adaptive in-flight system identification scheme has many advantages, including increased flight test efficiency, adaptability to dynamic characteristics that are imperfectly known a priori, in-flight improvement of data quality through iterative input design, and immediate feedback of the quality of flight test results. The technique uses equation error in the frequency domain with a recursive Fourier transform for the real time data analysis, and simple design methods employing square wave input forms to design the test inputs in flight. Simulation examples are used to demonstrate that the technique produces increasingly accurate model parameter estimates resulting from sequentially designed and implemented flight test maneuvers. The method has reasonable computational requirements, and could be implemented aboard an aircraft in real time.

Morelli, Eugene A.↗
NASA NTRS2009

Framework for Multidisciplinary Analysis, Design, and Optimization with High-Fidelity Analysis Tools

A plan is presented for the development of a high fidelity multidisciplinary optimization process for rotorcraft. The plan formulates individual disciplinary design problems, identifies practical high-fidelity tools and processes that can be incorporated in an automated optimization environment, and establishes statements of the multidisciplinary design problem including objectives, constraints, design variables, and cross-disciplinary dependencies. Five key disciplinary areas are selected in the development plan. These are rotor aerodynamics, rotor structures and dynamics, fuselage aerodynamics, fuselage structures, and propulsion / drive system. Flying qualities and noise are included as ancillary areas. Consistency across engineering disciplines is maintained with a central geometry engine that supports all multidisciplinary analysis. The multidisciplinary optimization process targets the preliminary design cycle where gross elements of the helicopter have been defined. These might include number of rotors and rotor configuration (tandem, coaxial, etc.). It is at this stage that sufficient configuration information is defined to perform high-fidelity analysis. At the same time there is enough design freedom to influence a design. The rotorcraft multidisciplinary optimization tool is built and substantiated throughout its development cycle in a staged approach by incorporating disciplines sequentially.

Orr, Stanley A.↗
DOE OSTI2025

Projection Analysis for ATR Irradiation of the AFC-FAST Experiment

Analyses of the Advanced Fuels Campaign Fission Accelerated Steady-state Test (AFC-FAST) in the Advanced Test Reactor are presented. A detailed methodology was employed to better account for uncertainties in the planned power and duration of sequential reactor loading cycles. By performing coupled depletion analyses at multiple power levels and durations, the differences in experiment heating outputs can be found. The effects of these uncertainties upon multiple experiment configurations were assessed in an effort to streamline the process of planning for and documenting future irradiations. In conclusion, the data generated from this work have been used to help inform assumptions on subsequent projections to perform only a nominal case depletion.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1995

Parallel Computational Environment for Substructure Optimization

Design optimization of large structural systems can be attempted through a substructure strategy when convergence difficulties are encountered. When this strategy is used, the large structure is divided into several smaller substructures and a subproblem is defined for each substructure. The solution of the large optimization problem can be obtained iteratively through repeated solutions of the modest subproblems. Substructure strategies, in sequential as well as in parallel computational modes on a Cray YMP multiprocessor computer, have been incorporated in the optimization test bed CometBoards. CometBoards is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for Design of Structures. Three issues, intensive computation, convergence of the iterative process, and analytically superior optimum, were addressed in the implementation of substructure optimization into CometBoards. Coupling between subproblems as well as local and global constraint grouping are essential for convergence of the iterative process. The substructure strategy can produce an analytically superior optimum different from what can be obtained by regular optimization. For the problems solved, substructure optimization in a parallel computational mode made effective use of all assigned processors.

Gendy, Atef S.↗