Multfidelity Estimators for Non-Deterministic Models
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Reuter, Bryan William↗
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Results for “DETERMINISTIC ESTIMATION”
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Probabilistic and deterministic aspects of linear estimation in geodesy
Recent advances in observational techniques related to geodetic work (VLBI, laser ranging) make it imperative that more consideration should be given to modeling problems. Uncertainties in the effect of atmospheric refraction, polar motion and precession-nutation parameters, cannot be dispensed with in the context of centimeter level geodesy. Even physical processes that have generally been previously altogether neglected (station motions) must now be taken into consideration. The problem of modeling functions of time or space, or at least their values at observation points (epochs) is explored. When the nature of the function to be modeled is unknown. The need to include a limited number of terms and to a priori decide upon a specific form may result in a representation which fails to sufficiently approximate the unknown function. An alternative approach of increasing application is the modeling of unknown functions as stochastic processes.
Dermanis, A.↗
Developing a New Model to Estimate the Costs to Decommission DOE's Active Facilities - 16368
The Active Facilities Data Collection System (AFDCS) is a major means the U.S. Department of Energy (DOE or Department) uses to estimate its out-year environmental liability for the active and surplus facilities across the Department. The previous AFDCS cost model was based on cost assumptions that date back to the mid-1990s. The model is being replaced with a model that reflects more recent facility disposition experience and costs. DOE's Office of Environmental Management's (DOE-EM) historical cost collection database provides the basis for the new AFDCS cost model. This paper describes the process that was used to update the AFDCS facility data inputs, analyze this data, and formulate historical costs and parameters. This process created a robust and reliable cost model that will provide DOE with a valid estimate of the facilities' disposition costs. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
MO-F-CAMPUS-I-01: A System for Automatically Calculating Organ and Effective Dose for Fluoroscopically-Guided Procedures
Purpose: A system was developed that automatically calculates the organ and effective dose for individual fluoroscopically-guided procedures using a log of the clinical exposure parameters. Methods: We have previously developed a dose tracking system (DTS) to provide a real-time color-coded 3D- mapping of skin dose. This software produces a log file of all geometry and exposure parameters for every x-ray pulse during a procedure. The data in the log files is input into PCXMC, a Monte Carlo program that calculates organ and effective dose for projections and exposure parameters set by the user. We developed a MATLAB program to read data from the log files produced by the DTS and to automatically generate the definition files in the format used by PCXMC. The processing is done at the end of a procedure after all exposures are completed. Since there are thousands of exposure pulses with various parameters for fluoroscopy, DA and DSA and at various projections, the data for exposures with similar parameters is grouped prior to entry into PCXMC to reduce the number of Monte Carlo calculations that need to be performed. Results: The software developed automatically transfers data from the DTS log file to PCXMC and runs the program for each grouping of exposure pulses. When the dose from all exposure events are calculated, the doses for each organ and all effective doses are summed to obtain procedure totals. For a complicated interventional procedure, the calculations can be completed on a PC without manual intervention in less than 30 minutes depending on the level of data grouping. Conclusion: This system allows organ dose to be calculated for individual procedures for every patient without tedious calculations or data entry so that estimates of stochastic risk can be obtained in addition to the deterministic risk estimate provided by the DTS. Partial support from NIH grant R01EB002873 and Toshiba Medical Systems Corp.
60 APPLIED LIFE SCIENCES↗
Delay compensation in integrated communication and control systems. I - Conceptual development and analysis
A procedure for compensating for the effects of distributed network-induced delays in integrated communication and control systems (ICCS) is proposed. The problem of analyzing systems with time-varying and possibly stochastic delays could be circumvented by use of a deterministic observer which is designed to perform under certain restrictive but realistic assumptions. The proposed delay-compensation algorithm is based on a deterministic state estimator and a linear state-variable-feedback control law. The deterministic observer can be replaced by a stochastic observer without any structural modifications of the delay compensation algorithm. However, if a feedforward-feedback control law is chosen instead of the state-variable feedback control law, the observer must be modified as a conventional nondelayed system would be. Under these circumstances, the delay compensation algorithm would be accordingly changed. The separation principle of the classical Luenberger observer holds true for the proposed delay compensator. The algorithm is suitable for ICCS in advanced aircraft, spacecraft, manufacturing automation, and chemical process applications.
Luck, Rogelio↗
LandScan mosaic enables high-resolution gridded population estimates with explicit uncertainty
Gridded population datasets represent high-resolution distributions of human occupancy, enabling informed decision-making across a broad range of fields. These data products are valuable for assessing environmental risk, urban development, disaster preparedness and resource allocation—areas where accurate population estimates directly enhance policy effectiveness and optimize resource distribution. Despite the importance of gridded population datasets, traditional population modeling approaches often overlook inherent uncertainties in the estimation process. This limitation can create a false sense of certainty in population estimates, potentially leading to flawed decisions by those who rely on the data. To address this methodological gap, we introduce a probabilistic machine learning modeling framework, LandScan Mosaic, that explicitly incorporates uncertainty into the population modeling process. Our approach systematically quantifies uncertainty in three key modeling parameters of the LandScan HD gridded population dataset: building use types, floor counts, and occupancy rates. By employing Monte Carlo simulations, we propagate these uncertainties through the modeling process, yielding probability distributions of population counts in place of deterministic point estimates. We demonstrate the practical application of this framework in Iloilo City, Philippines, using structured decision-making techniques and our probabilistic estimates to identify and prioritize areas most affected by projected flooding, supporting targeted interventions that address both economic and social risks. In doing so, we propose a population-specific approach for incorporating confidence into structured decision making processes. Through a comparative analysis with conventional deterministic approaches and point estimate approaches, including LandScan HD and WorldPop, we evaluate how the incorporation of machine learning and uncertainty influences decision rankings. This research advances population distribution modeling by offering a robust, quantitative approach that explicitly accounts for uncertainty in the underlying data, along with guidance for how users can apply uncertainty in their decision-making.
Environmental sciences↗
Implementation of Gy-Eq for deterministic effects limitation in shield design
The NCRP has recently defined RBE values and a new quantity (Gy-Eq) for use in estimation of deterministic effects in space shielding and operations. The NCRP's RBE for neutrons is left ambiguous and not fully defined. In the present report we will suggest a complete definition of neutron RBE consistent with the NCRP recommendations and evaluate attenuation properties of deterministic effects (Gy-Eq) in comparison with other dosimetric quantities.
NASA Discipline Radiation Health↗
A partially reflecting random walk on spheres algorithm for electrical impedance tomography
In this work, we develop a probabilistic estimator for the voltage-to-current map arising in electrical impedance tomography. This novel so-called partially reflecting random walk on spheres estimator enables Monte Carlo methods to compute the voltage-to-current map in an embarrassingly parallel manner, which is an important issue with regard to the corresponding inverse problem. Our method uses the well-known random walk on spheres algorithm inside subdomains where the diffusion coefficient is constant and employs replacement techniques motivated by finite difference discretization to deal with both mixed boundary conditions and interface transmission conditions. We analyze the global bias and the variance of the new estimator both theoretically and experimentally. Subsequently, the variance of the new estimator is considerably reduced via a novel control variate conditional sampling technique which yields a highly efficient hybrid forward solver coupling probabilistic and deterministic algorithms.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Parameter estimation in linear models of the human operator in a closed loop with application of deterministic test signals
Parameter estimation techniques are discussed with emphasis on unbiased estimates in the presence of noise. A distinction between open and closed loop systems is made. A method is given based on the application of external forcing functions consisting of a sun of sinusoids; this method is thus based on the estimation of Fourier coefficients and is applicable for models with poles and zeros in open and closed loop systems.
Vanlunteren, A.↗
Assessment and uncertainty analysis of groundwater risk
Highlights: • Two different sets of index evaluation systems for shallow and deep groundwater were built respectively. • Ordinary kriging was adopted to execute the interpolation estimation. • The synthetic weights were adopted merging the AHP method and PCA method. • The uncertainty of groundwater risk was analyzed by indicator kriging. Groundwater with relatively stable quantity and quality is commonly used by human being. However, as the over-mining of groundwater, problems such as groundwater funnel, land subsidence and salt water intrusion have emerged. In order to avoid further deterioration of hydrogeological problems in over-mining regions, it is necessary to conduct the assessment of groundwater risk. In this paper, risks of shallow and deep groundwater in the water intake area of the South-to-North Water Transfer Project in Tianjin, China, were evaluated. Firstly, two sets of four-level evaluation index system were constructed based on the different characteristics of shallow and deep groundwater. Secondly, based on the normalized factor values and the synthetic weights, the risk values of shallow and deep groundwater were calculated. Lastly, the uncertainty of groundwater risk assessment was analyzed by indicator kriging method. The results meet the decision maker's demand for risk information, and overcome previous risk assessment results expressed in the form of deterministic point estimations, which ignore the uncertainty of risk assessment.
54 ENVIRONMENTAL SCIENCES↗
Hybrid approaches for multiple-species stochastic reaction–diffusion models
Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Stochastic level-set method for shape optimisation
We present a new method for stochastic shape optimisation of engineering structures. The method generalises an existing deterministic scheme, in which the structure is represented and evolved by a level-set method coupled with mathematical programming. The stochastic element of the algorithm is built on the methods of statistical mechanics and is designed so that the system explores a Boltzmann–Gibbs distribution of structures. In non-convex optimisation problems, the deterministic algorithm can get trapped in local optima: the stochastic generalisation enables sampling of multiple local optima, which aids the search for the globally-optimal structure. The method is demonstrated for several simple geometrical problems, and a proof-of-principle calculation is shown for a simple engineering structure.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
A hybrid Monte Carlo, discontinuous Galerkin method for linear kinetic transport equations
Here we present a hybrid method for time-dependent particle transport problems that combines Monte Carlo (MC) estimation with deterministic solutions based on discrete ordinates. For spatial discretizations, the MC algorithm computes a piecewise constant solution and the discrete ordinates use bilinear discontinuous finite elements. From the hybridization of the problem, the resulting problem solved by Monte Carlo is scattering free, resulting in a simple, efficient solution procedure. Between time steps, we use a projection approach to “relabel” collided particles as uncollided particles. In conclusion, from a series of standard 2-D Cartesian test problems we observe that our hybrid method has improved accuracy and reduction in computational complexity of approximately an order of magnitude relative to standard discrete ordinates solutions.
97 MATHEMATICS AND COMPUTING↗
Chaos in an imperfectly premixed model combustor
This article reports nonlinear bifurcations observed in a laboratory scale, turbulent combustor operating under imperfectly premixed mode with global equivalence ratio as the control parameter. The results indicate that the dynamics of thermoacoustic instability correspond to quasi-periodic bifurcation to low-dimensional, deterministic chaos, a route that is common to a variety of dissipative nonlinear systems. The results support the recent identification of bifurcation scenarios in a laminar premixed flame combustor (Kabiraj et al., Chaos: Interdiscip. J. Nonlinear Sci. 22, 023129 (2012)) and extend the observation to a practically relevant combustor configuration.
42 ENGINEERING↗
Efficient block processing of long duration biotelemetric brain data for health care monitoring
In real time clinical environment, the brain signals which doctor need to analyze are usually very long. Such a scenario can be made simple by partitioning the input signal into several blocks and applying signal conditioning. This paper presents various block based adaptive filter structures for obtaining high resolution electroencephalogram (EEG) signals, which estimate the deterministic components of the EEG signal by removing noise. To process these long duration signals, we propose Time domain Block Least Mean Square (TDBLMS) algorithm for brain signal enhancement. In order to improve filtering capability, we introduce normalization in the weight update recursion of TDBLMS, which results TD-B-normalized-least mean square (LMS). To increase accuracy and resolution in the proposed noise cancelers, we implement the time domain cancelers in frequency domain which results frequency domain TDBLMS and FD-B-Normalized-LMS. Finally, we have applied these algorithms on real EEG signals obtained from human using Emotive Epoc EEG recorder and compared their performance with the conventional LMS algorithm. The results show that the performance of the block based algorithms is superior to the LMS counter-parts in terms of signal to noise ratio, convergence rate, excess mean square error, misadjustment, and coherence.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
A fixed mass method for the Kramers-Moyal expansion—Application to time series with outliers
Extraction of stochastic and deterministic components from empirical data—necessary for the reconstruction of the dynamics of the system—is discussed. We determine both components using the Kramers-Moyal expansion. In our earlier papers, we obtained large fluctuations in the magnitude of both terms for rare or extreme valued events in the data. Calculations for such events are burdened by an unsatisfactory quality of the statistics. In general, the method is sensitive to the binning procedure applied for the construction of histograms. Instead of the commonly used constant width of bins, we use here a constant number of counts for each bin. This approach—the fixed mass method—allows to include in the calculation events, which do not yield satisfactory statistics in the fixed bin width method. The method developed is general. To demonstrate its properties, here, we present the modified Kramers-Moyal expansion method and discuss its properties by the application of the fixed mass method to four representative heart rate variability recordings with different numbers of ectopic beats. These beats may be rare events as well as outlying, i.e., very small or very large heart cycle lengths. The properties of ectopic beats are important not only for medical diagnostic purposes but the occurrence of ectopic beats is a general example of the kind of variability that occurs in a signal with outliers. To show that the method is general, we also present results for two examples of data from very different areas of science: daily temperatures at a large European city and recordings of traffics on a highway. Using the fixed mass method, to assess the dynamics leading to the outlying events we studied the occurrence of higher order terms of the Kramers-Moyal expansion in the recordings. We found that the higher order terms of the Kramers-Moyal expansion are negligible for heart rate variability. This finding opens the possibility of the application of the Langevin equation to the whole range of empirical signals containing rare or outlying events. Note, however, that the higher order terms are non-negligible for the other data studied here and for it the Langevin equation is not applicable as a model.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Risk-Informed Safety Analysis for Accident Tolerant Fuels
Accident Tolerant Fuels (ATF) are being tested by different nuclear vendors and research organizations and their introduction in the US light water reactors fleet is planned for the second half of the 2020`s. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Systems Analysis pathway, researches are being conducted at the Idaho National Laboratory for developing tools and methods that can help the industry quantifying the benefits from the adoption of ATF technology. In this paper we describe the developed risk-informed methodology including the safety analysis codes improvements, and we present some results for selected accident scenarios. The developed methodology combines INL state-of-the-art deterministic Best Estimate code RELAP5-3D, and Probabilistic Risk Analysis tools RAVEN and SAPHIRE. The analyses are performed on a three-loops pressurized water reactor, simulating Station Blackout and LB-LOCA accidents and considering near-term ATFs, or FeCrAl and Chromium-coated clads. Finally, we show how, applying our methodology, the new Core Damage Frequency can be assessed. The results indicated that the main benefits in introducing near-term ATFs concern a significant reduction in the hydrogen production during accident conditions. No significant Core Damage Frequency reduction was found.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Risk-Informed Safety Analysis for Accident Tolerant Fuels
Accident Tolerant Fuels (ATF) are being tested by different nuclear vendors and research organization and their introduction in light water reactors fleet is planned for the second half of the 2020`s. In the framework of the US-DOE Light-Water Reactor Sustainability program, Risk-Informed Safety Analysis pathway (LWRS-RISA), research activities are being conducted at the Idaho National Laboratory (INL) for developing tools and methods that can help the industry in quantifying the ATF introduction benefits. In this paper we describe the developed risk-informed methodology, the codes improvements and we present some results for selected accidental conditions. The developed methodology combines INL state-of-the-art deterministic Best Estimate tools like RELAP5-3D code, and Probabilistic Risk Analysis tools like RAVEN and SAPHIRE codes. The analyses are performed on a three-loops pressurized water reactor (PWR) simulating accidental conditions like Station Blackout and LB-LOCA and considering near-term ATF (FeCrAl and Chromium-coated clads). Finally, we show, through our methodologies, how the delta-Core Damage Frequency can be assessed.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗