Results for “Deterministic processes” — Page 3

NASA NTRS2014

Integrated Arrival and Departure Schedule Optimization Under Uncertainty

In terminal airspace, integrating arrivals and departures with shared waypoints provides the potential of improving operational efficiency by allowing direct routes when possible. Incorporating stochastic evaluation as a post-analysis process of deterministic optimization, and imposing a safety buffer in deterministic optimization, are two ways to learn and alleviate the impact of uncertainty and to avoid unexpected outcomes. This work presents a third and direct way to take uncertainty into consideration during the optimization. The impact of uncertainty was incorporated into cost evaluations when searching for the optimal solutions. The controller intervention count was computed using a heuristic model and served as another stochastic cost besides total delay. Costs under uncertainty were evaluated using Monte Carlo simulations. The Pareto fronts that contain a set of solutions were identified and the trade-off between delays and controller intervention count was shown. Solutions that shared similar delays but had different intervention counts were investigated. The results showed that optimization under uncertainty could identify compromise solutions on Pareto fonts, which is better than deterministic optimization with extra safety buffers. It helps decision-makers reduce controller intervention while achieving low delays.

stochastic optimization↗

NASA NTRSDate not supplied

A System to Provide Deterministic Flight Software Operation and Maximize Multicore Processing Performance: The Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) Datapath

A method and design are described for a system that processes multiple data streams, utilizing a multicore asymmetric processing architecture, that eliminates data interrupts to the application processors. The design supports a deterministic environment for flight software in NASA’s Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) project. The SPLICE project develops sensor, algorithm, and compute technologies for Precision Landing and Hazard Avoidance (PL&HA) capabilities. The compute technology for SPLICE is the Descent and Landing Computer (DLC). The DLC hosts several SPLICE algorithms with high computational resource requirements that must be executed in a real-time and deterministic manner. The software runs on a custom Single Board Computer (SBC), with a Xilinx Ultrascale+ Multiprocessor System-on-a-Chip (MPSoC). Input data for the flight software is from a variety of sensors, unique with respect to data rate and packet size. A data path between the SPLICE sensors and algorithms is designed to efficiently deliver this data to the flight software using the MPSoC asymmetric processing cores and Field Programmable Gate Array (FPGA) fabric. This is implemented in a manner that isolates the application processors running the flight software from interrupts associated with the input data. By leveraging real-time processors on the MPSoC, and a structure with the appropriate interfaces in the shared memory on the SBC, the flight software can use the full set of application processors. The available utilization for each processor in this set is also maximized for the SPLICE applications, providing a sufficiently deterministic execution environment without the cost and overhead of a real-time operating system.

heterogeneous processing system↗

NASA NTRS1984

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Arduini, R. F.↗

NASA NTRS1982

Study of sensor spectral responses and data processing algorithms and architectures for onboard feature identification

A computational model of the deterministic and stochastic processes involved in remote sensing is used to study spectral feature identification techniques for real-time onboard processing of data acquired with advanced earth-resources sensors. Preliminary results indicate that: Narrow spectral responses are advantageous; signal normalization improves mean-square distance (MSD) classification accuracy but tends to degrade maximum-likelihood (MLH) classification accuracy; and MSD classification of normalized signals performs better than the computationally more complex MLH classification when imaging conditions change appreciably from those conditions during which reference data were acquired. The results also indicate that autonomous categorization of TM signals into vegetation, bare land, water, snow and clouds can be accomplished with adequate reliability for many applications over a reasonably wide range of imaging conditions. However, further analysis is required to develop computationally efficient boundary approximation algorithms for such categorization.

Huck, F. O.↗

NASA NTRS2023

A System to Provide Deterministic Flight Software Operation and Maximize Multicore Processing Performance: The Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) Datapath

A method and design are described for a system that processes multiple data streams, utilizing a multicore asymmetric processing architecture, that eliminates data interrupts to the application processors. The design supports a deterministic environment for flight software in NASA’s Safe and Precise Landing – Integrated Capabilities Evolution (SPLICE) project. The SPLICE project develops sensor, algorithm, and compute technologies for Precision Landing and Hazard Avoidance (PL&HA) capabilities. The compute technology for SPLICE is the Descent and Landing Computer (DLC). The DLC hosts several SPLICE algorithms with high computational resource requirements that must be executed in a real-time and deterministic manner. The software runs on a custom Single Board Computer (SBC), with a Xilinx Ultrascale+ Multiprocessor System-on-a-Chip (MPSoC). Input data for the flight software is from a variety of sensors, unique with respect to data rate and packet size. A data path between the SPLICE sensors and algorithms is designed to efficiently deliver this data to the flight software using the MPSoC asymmetric processing cores and Field Programmable Gate Array (FPGA) fabric. This is implemented in a manner that isolates the application processors running the flight software from interrupts associated with the input data. By leveraging real-time processors on the MPSoC, and a structure with the appropriate interfaces in the shared memory on the SBC, the flight software can use the full set of application processors. The available utilization for each processor in this set is also maximized for the SPLICE applications, providing a sufficiently deterministic execution environment without the cost and overhead of a real-time operating system.

David K. Rutishauser↗

NASA NTRS1987

Effects of intensity modulations on the power spectra of random processes

Intensity-modulated random processes (IMRPs), defined as the products of (1) deterministic modulating functions or processes and (2) stationary modulated processes statistically independent of (1), are investigated analytically. Instantaneous power spectra are derived for IMRPs with different classes of (1), and a spectrum series expansion with a known locally stationary approximation as its first term is obtained. Numerical results for sample IMRPs with known (deterministic), stationary, nonstationary, ergodic, onset, and bell-shaped types of (1) are presented graphically and briefly characterized.

Mark, W. D.↗

NASA NTRS2010

Computer-Controlled Cylindrical Polishing Process for Large X-Ray Mirror Mandrels

We are developing high-energy grazing incidence shell optics for hard-x-ray telescopes. The resolution of a mirror shells depends on the quality of cylindrical mandrel from which they are being replicated. Mid-spatial-frequency axial figure error is a dominant contributor in the error budget of the mandrel. This paper presents our efforts to develop a deterministic cylindrical polishing process in order to keep the mid-spatial-frequency axial figure errors to a minimum. Simulation software is developed to model the residual surface figure errors of a mandrel due to the polishing process parameters and the tools used, as well as to compute the optical performance of the optics. The study carried out using the developed software was focused on establishing a relationship between the polishing process parameters and the mid-spatial-frequency error generation. The process parameters modeled are the speeds of the lap and the mandrel, the tool s influence function, the contour path (dwell) of the tools, their shape and the distribution of the tools on the polishing lap. Using the inputs from the mathematical model, a mandrel having conical approximated Wolter-1 geometry, has been polished on a newly developed computer-controlled cylindrical polishing machine. The preliminary results of a series of polishing experiments demonstrate a qualitative agreement with the developed model. We report our first experimental results and discuss plans for further improvements in the polishing process. The ability to simulate the polishing process is critical to optimize the polishing process, improve the mandrel quality and significantly reduce the cost of mandrel production

Khan, Gufran S.↗

DOE OSTI2021

Accurate Simulation of Both Sensitivity and Variability for Amazonian Photosynthesis: Is It Too Much to Ask?

Abstract Estimates of Amazon rainforest gross primary productivity (GPP) differ by a factor of 2 across a suite of three statistical and 18 process models. This wide spread contributes uncertainty to predictions of future climate. We compare the mean and variance of GPP from these models to that of GPP at six eddy covariance (EC) towers. Only one model's mean GPP across all sites falls within a 99% confidence interval for EC GPP, and only one model matches EC variance. The strength of model response to climate drivers is related to model ability to match the seasonal pattern of the EC GPP. Models with stronger seasonal swings in GPP have stronger responses to rain, light, and temperature than does EC GPP. The model to data comparison illustrates a trade‐off inherent to deterministic models between accurate simulation of a mean (average) and accurate responsiveness to drivers. The trade‐off exists because all deterministic models simplify processes and lack at least some consequential driver or interaction. If a model's sensitivities to included drivers and their interactions are accurate, then deterministically predicted outcomes have less variability than is realistic. If a GPP model has stronger responses to climate drivers than found in data, model predictions may match the observed variance and seasonal pattern but are likely to overpredict GPP response to climate change. High or realistic variability of model estimates relative to reference data indicate that the model is hypersensitive to one or more drivers.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2010

Design Considerations of Polishing Lap for Computer-Controlled Cylindrical Polishing Process

The future X-ray observatory missions, such as International X-ray Observatory, require grazing incidence replicated optics of extremely large collecting area (3 m2) in combination with angular resolution of less than 5 arcsec half-power diameter. The resolution of a mirror shell depends ultimately on the quality of the cylindrical mandrels from which they are being replicated. Mid-spatial-frequency axial figure error is a dominant contributor in the error budget of the mandrel. This paper presents our efforts to develop a deterministic cylindrical polishing process in order to keep the mid-spatial-frequency axial figure errors to a minimum. Simulation studies have been performed to optimize the operational parameters as well as the polishing lap configuration. Furthermore, depending upon the surface error profile, a model for localized polishing based on dwell time approach is developed. Using the inputs from the mathematical model, a mandrel, having conical approximated Wolter-1 geometry, has been polished on a newly developed computer-controlled cylindrical polishing machine. We report our first experimental results and discuss plans for further improvements in the polishing process.

Khan, Gufran S.↗

NASA NTRS2000

A Pulse-Compression Method for Process Monitoring

This paper describes, from a deterministic view point, an on-line process monitoring method for small signal behavior of time invariant stable systems at a given operating point. The monitoring is accomplished by using an consequence modulated low-pass wavelet as the probing signal, and a cyclic reference signal as the correlator. This method allows to achieve high resolution, high signal to noise ratio monitoring, and the acquired data can be used for on-line diagnosis.

Wu, N. Eva↗

DOE OSTI2024

DECOVALEX-2023: Task F2 Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2- (salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics. Thermal, hydrological, mechanical, and chemical properties of individual components of the engineered and natural system were chosen for relevance by participating teams. The salt reference case system was characterized using data and measurements collected at relevant underground research laboratories (URLs), field sites, and simulation results from teams with specialized modelling capability. Participating teams made a wide range of model assumptions from compartmentalized networks to full 3D models of the salt formation. No single contributed model includes full-fidelity representation of all the features, events, and processes (FEPs) detailed in the task specification, but almost all features and processes are represented in at least one model. Despite differences in the modelling strategies developed by participating teams, all models indicate that salt compaction and radionuclide diffusion are key processes in the repository, and for the FEPs and model scenario considered, little of the disposed radionuclides will migrate beyond the repository seal over the 100,000 year simulations. In general, the model output quantities have the largest differences over the short term and near the waste. The models tend to be more similar further from waste and at later time. Disparities between the models are believed to be due to differing simplifications from the task specification, some of which are chosen simplifications to reduce complexity, and some are restrictions imposed by the modelling tools. A second round of this task has been accepted for DECOVALEX-2027 in conjunction with Task F1 on crystalline PA modelling. The future round includes waste package heating, improved modelling of salt creep closure, additional comparisons of coupled-process sub-models, and the impact of repository engineering design on radionuclide migration in the repository. Participants will also propose and finalize a set of uncertain inputs for the reference case simulations, propagate these uncertainties in a set of realizations, and conduct sensitivity analyses on the simulation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Comprehensive Battery Safety Risk Evaluation: Aged Cells versus Fresh Cells Upon Mechanical Abusive Loadings

Abstract Despite their wide applications, lithium‐ion batteries (LIBs) have been struggling with their safety risks arising from different lifetime stages. Here, the NCMA pouch cell is taken as an example, and the safety of both fresh and aged cells from three milestone stages, that is, internal short circuit (ISC) triggering risk, ISC mode, and the subsequent thermal runaway (TR) consequence is investigated. By combining mechanical abusive testing and physics‐based models on commercialized cells with various states‐of‐health (SOH) and states‐of‐charge, it is discovered that the ISC triggering delays with the decay of SOH and soft ISC mode will be triggered more frequently, which is mainly due to the mechanical behaviors of the current collectors. The temperature rises and peak temperature during the subsequent TR also become milder for aged cells due to the reduced capacity and deterministic soft ISC process. Results here provide a mechanistic explanation of the safety risk comparison between the fresh and aged cells, offering cornerstone guidance to the evaluation and design of next‐generation safer LIBs.

25 ENERGY STORAGE↗

DOE OSTI2023

Stochastic projective splitting

Here, we present a new, stochastic variant of the projective splitting (PS) family of algorithms for inclusion problems involving the sum of any finite number of maximal monotone operators. This new variant uses a stochastic oracle to evaluate one of the operators, which is assumed to be Lipschitz continuous, and (deterministic) resolvents to process the remaining operators. Our proposal is the first version of PS with such stochastic capabilities. We envision the primary application being machine learning (ML) problems, with the method’s stochastic features facilitating “mini-batch” sampling of datasets. Since it uses a monotone operator formulation, the method can handle not only Lipschitz-smooth loss minimization, but also min–max and noncooperative game formulations, with better convergence properties than the gradient descent-ascent methods commonly applied in such settings. The proposed method can handle any number of constraints and nonsmooth regularizers via projection and proximal operators. We prove almost-sure convergence of the iterates to a solution and a convergence rate result for the expected residual, and close with numerical experiments on a distributionally robust sparse logistic regression problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Modeling and simulation of vascular tumors embedded in evolving capillary networks

Here in this work, we present a coupled 3D–1D model of solid tumor growth within a dynamically changing vascular network to facilitate realistic simulations of angiogenesis. Additionally, the model includes erosion of the extracellular matrix, interstitial flow, and coupled flow in blood vessels and tissue. We employ continuum mixture theory with stochastic Cahn–Hilliard type phase-field models of tumor growth. The interstitial flow is governed by a mesoscale version of Darcy’s law. The flow in the blood vessels is controlled by Poiseuille flow, and Starling’s law is applied to model the mass transfer in and out of blood vessels. The evolution of the network of blood vessels is orchestrated by the concentration of the tumor angiogenesis factors (TAFs); blood vessels grow towards the increasing TAFs concentrations. This process is not deterministic, allowing random growth of blood vessels and, therefore, due to the coupling of nutrients in tissue and vessels, makes the growth of tumors stochastic. We demonstrate the performance of the model by applying it to a variety of scenarios. Numerical experiments illustrate the flexibility of the model and its ability to generate satellite tumors. Simulations of the effects of angiogenesis on tumor growth are presented as well as sample-independent features of cancer.

3D–1D coupled blood flow models↗

DOE OSTI2021

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

DOE OSTI2023

DECOVALEX-2023: Task F2-Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2-(salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1979

Application of queueing models to multiprogrammed computer systems operating in a time-critical environment

A model of a central processor (CPU) which services background applications in the presence of time critical activity is presented. The CPU is viewed as an M/M/1 queueing system subject to periodic interrupts by deterministic, time critical process. The Laplace transform of the distribution of service times for the background applications is developed. The use of state of the art queueing models for studying the background processing capability of time critical computer systems is discussed and the results of a model validation study which support this application of queueing models are presented.

Eckhardt, D. E., Jr.↗

NASA NTRS1982

Computational modeling for the study of multispectral sensor systems and concepts

A computational model of the deterministic and stochastic processes involved in remote sensing is being developed as a tool for studying multispectral sensor systems and concepts. The goal is to improve the efficiency of sensor systems for routine worldwide monitoring of earth resources and the environment. Preliminary computational results are presented for simple models of the natural variability of atmospheric radiative transfer and surface reflectance. These results illustrate the dependence of classification accuracy on the selection of sensor spectral channels and data processing algorithms.

Huck, F. O.↗