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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Fluctuant storage temperature increased the heterogeneous distributions of pH and fermentation products in large round bale silage

Abstract In practical of silage production, variations in the fermentation parameters of silage might be attributable to changes in weather data, especially for ambient temperature. The objective of this study was to investigate how the changed temperature of outside weather condition affects distributions of pH and fermentation products in large round bale silage. The bale silages (1.22 m × 1.25 m ø; density, about 168.9 kg dry matter [DM]/m 3 ) were produced by BR6090 Combi from New Holland Agriculture, wrapped with six layers of stretch film, stored at ambient temperature (2–20°C) and constant temperature (10°C; 15°C; 25°C) for 3, 9, 15, 45 and 90 days. Compared with other silages, silage stored at 25°C had higher ( p < 0.05) lactic acid content, lower ( p < 0.05) pH, butyric acid content and ammonia‐nitrogen (N) ratio of total N. Fluctuant storage temperature limited lactic acid fermentation process with delayed pH decline and continuous butyric production and crude protein (CP) degradation. The differences of pH, lactic acid, propionic acid and ammonia‐N were considerably less evident in the centre of silages stored at different temperatures, and they increased towards the boundaries. The data shows that fluctuant storage temperature had undesirable effect on the fermentation quality of silage, especially for the external part of silo; relatively high and stable storage temperature for initial stage of ensiling process was necessary, but did not promote a positive response to the homogeneous distributions of pH and fermentation products in large round bale silage.

Li, Ping↗
DOE OSTI2016

Optical arc sensor using energy harvesting power source

Wireless sensors without external power supply gained considerable attention due to convenience both in installation and operation. Optical arc detecting sensor equipping with self sustaining power supply using energy harvesting method was investigated. Continuous energy harvesting method was attempted using thermoelectric generator to supply standby power in micro ampere scale and operating power in mA scale. Peltier module with heat-sink was used for high efficiency electricity generator. Optical arc detecting sensor with hybrid filter showed insensitivity to fluorescent and incandescent lamps under simulated distribution panel condition. Signal processing using integrating function showed selective arc discharge detection capability to different arc energy levels, with a resolution below 17 J energy difference, unaffected by bursting arc waveform. The sensor showed possibility for application to arc discharge detecting sensor in power distribution panel. Also experiment with proposed continuous energy harvesting method using thermoelectric power showed possibility as a self sustainable power source of remote sensor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

The soil health assessment protocol and evaluation applied to soil organic carbon

The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site-specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Scale Mixtures of Frechet Distributions as Asymptotic Approximations of Extreme Precipitation

This paper is a further development of the results of [20] where, based on the negative binomial model for the duration of wet periods measured in days [16], an asymptotic approximation was proposed for the distribution of the maximum daily precipitation volume within a wet period. This approximation has the form of a scale mixture of the Fr´echet distribution with the gamma mixing distribution and coincides with the distribution of a positive power of a random variable having the Snedecor–Fisher distribution. Here we extend this result to the mth extremes, m ∈ ℕ, and sample quantiles. The proof of this result is based on the representation of the negative binomial distribution as a mixed geometric (and hence, mixed Poisson) distribution [17] and limit theorems for extreme order statistics in samples with random sizes having mixed Poisson distributions [10]. Some analytic properties of the obtained limit distribution are described. In particular, it is demonstrated that under certain conditions the limit distribution of the maximum precipitation is mixed exponential and hence, is infinitely divisible. It is shown that under the same conditions this limit distribution can be represented as a scale mixture of stable or Weibull or Pareto or folded normal laws. The corresponding product representations for the limit random variable can be used for its computer simulation. The results of fitting this distribution to real data are presented illustrating high adequacy of the proposed model. It is also shown that the limit distribution of sample quantiles is the well-known Student distribution. Several methods are proposed for the estimation of the parameters of the asymptotic distributions. The obtained mixture representations for the limit laws and the corresponding asymptotic approximations provide better insight into the nature of mixed probability (“Bayesian”) models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Variable Selection for High Dimensional Bayesian Density Estimation: Application to Human Exposure Simulation

Summary Numerous studies have linked ambient air pollution and adverse health outcomes. Many studies of this nature relate outdoor pollution levels measured at a few monitoring stations with health outcomes. Recently, computational methods have been developed to model the distribution of personal exposures, rather than ambient concentration, and then relate the exposure distribution to the health outcome. Although these methods show great promise, they are limited by the computational demands of the exposure model. We propose a method to alleviate these computational burdens with the eventual goal of implementing a national study of the health effects of air pollution exposure. Our approach is to develop a statistical emulator for the exposure model, i.e. we use Bayesian density estimation to predict the conditional exposure distribution as a function of several variables, such as temperature, human activity and physical characteristics of the pollutant. This poses a challenging statistical problem because there are many predictors of the exposure distribution and density estimation is notoriously difficult in high dimensions. To overcome this challenge, we use stochastic search variable selection to identify a subset of the variables that have more than just additive effects on the mean of the exposure distribution. We apply our method to emulate an ozone exposure model in Philadelphia.

Reich, Brian J.↗
DOE OSTI2018

In Situ Modification and Analysis of the Composition and Crystal Structure of a Silicon Target by Ion-Beam Methods

The method of Rutherford backscattering (RBS) with channeling is widely used in compositional analysis and structural determination. An experimental process line for in situ ion implantation and RBS spectrometry is presented, and its technical parameters are given. The parameters of a probing beam needed to reach a several-percent error in the study of distribution profiles of impurities and defects are detailed. The resolution of this method was estimated using the spectrum of alpha particles produced in the decay of {sup 239}Pu and based on the RBS spectrum from a silicon monocrystal. The implantation of Xe{sup +} ions with an energy of 100 keV into a silicon monocrystal and the RBS analysis of targets in the channeling mode were performed without breach of vacuum conditions. The distribution profiles of implanted atoms and defects in irradiated monocrystals were examined.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Proposed Algorithm for Placement and Sizing of Generation and Storage Stations in Urban Environments

The placement of generation and storage stations (GSSs) in distribution grids has been extensively investigated. Most traditional methods are applicable to rural or homogeneous environments and do not account for external restrictions on generation placement in urban or semi-urban environments. In this article, we propose a method for generation placement considering externality constraints. New utility-scale generation in distribution grids potentially occupies footprint and interferes in areas with existing infrastructure with architectural, historical, or touristic value. Urban environments are often regulated by municipal legislation. The placement of utility-scale generation in urban landscapes is economically and physically restricted by such externalities, and existing methods for generation placement in distribution grids based on technical optimization fail to account for this important nuance. The proposed algorithm flexibly adapts to changes in government energy policies and priorities. The selection of the type of generation suitable for the power grid is left to the preference of external high-level stakeholders, such as urban planners, industry development leaders, and energy policymakers. The proposed algorithm is a unique tool for determining the placement and sizing of generation in realistic conditions in distribution grids; it is adaptable to urban externalities and sensitive to stakeholder preferences.

generation and storage station placement↗
DOE OSTI2014

A budget and accounting of metals at z ∼ 0: Results from the COS-Halos survey

We present a budget and accounting of metals in and around star-forming galaxies at z ∼ 0. We combine empirically derived star formation histories with updated supernova and asymptotic giant branch yields and rates to estimate the total mass of metals produced by galaxies with present-day stellar mass of 10{sup 9.3}-10{sup 11.6} M{sub ☉}. On the accounting side of the ledger, we show that a surprisingly constant 20%-25% mass fraction of produced metals remain in galaxies' stars, interstellar gas and interstellar dust, with little dependence of this fraction on the galaxy stellar mass (omitting those metals immediately locked up in remnants). Thus, the bulk of metals are outside of galaxies, produced in the progenitors of today's L* galaxies. The COS-Halos survey is uniquely able to measure the mass of metals in the circumgalactic medium (CGM, to impact parameters of <150 kpc) of low-redshift ∼L* galaxies. Using these data, we map the distribution of CGM metals as traced by both the highly ionized O VI ion and a suite of low-ionization species; combined with constraints on circumgalactic dust and hotter X-ray emitting gas out to similar impact parameters, we show that ∼40% of metals produced by M {sub *} ∼ 10{sup 10} M{sub ☉} galaxies can be easily accounted for out to 150 kpc. With the current data, we cannot rule out a constant mass of metals within this fixed physical radius. This census provides a crucial boundary condition for the eventual fate of metals in galaxy evolution models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Generative Adversarial Network for Synthetic Time Series Data Generation in Smart Grids

The availability of fine grained time series data is a pre-requisite for research in smart-grids. While data for transmission systems is relatively easily obtainable, issues related to data collection, security and privacy hinder the widespread public availability/accessibility of such datasets at the distribution system level. This has prevented the larger research community from effectively applying sophisticated machine learning algorithms to significantly improve the distribution-level accuracy of predictions and increase the efficiency of grid operations. Synthetic dataset generation has proven to be a promising solution for addressing data availability issues in various domains such as computer vision, natural language processing and medicine. However, its exploration in the smart grid context remains unsatisfactory. Previous works have tried to generate synthetic datasets by modeling the underlying system dynamics: an approach which is difficult, time consuming, error prone and often times infeasible in many problems. In this work, we propose a novel data-driven approach to synthetic dataset generation by utilizing deep generative adversarial networks (GAN) to learn the conditional probability distribution of essential features in the real dataset and generate samples based on the learned distribution. To evaluate our synthetically generated dataset, we measure the maximum mean discrepancy (MMD) between real and synthetic datasets as probability distributions, and show that their sampling distance converges. To further validate our synthetic dataset, we perform common smart grid tasks such as k-means clustering and short-term prediction on both datasets. Experimental results show the efficacy of our synthetic dataset approach: the real and synthetic datasets are indistinguishable by solely examining the output of these tasks.

14 SOLAR ENERGY↗
DOE OSTI2021

Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models

Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

DECOVALEX-2023: Task D Final Report

Task D of DECOVALEX-2023 is focused on the simulation of the coupled thermal hydraulic-mechanical (THM) behaviour in the full-scale engineered barrier system (EBS). The Horonobe EBS experiment is the demonstration of the full-scale EBS in the underground research laboratory (URL) (performed by JAEA in the Horonobe URL in Japan). Task D consisted of the three steps, a preliminary step (Step 0), simulation of the laboratory tests (Step 1) and simulation of the in-situ full-scale EBS experiment (Step 2). Since the Horonobe EBS experiment demonstrates the vertical emplacement option of the EBS, the experiment gallery is also backfilled with the backfill material. Therefore, interaction between the EBS and the backfill material can also be demonstrated, such as deformation (change of density) of the buffer material. The underground water in the Horonobe URL is saline. This fact adds chemical processes to THM behaviour. For example, mechanical properties (such as swelling pressure of the buffer material and backfill material) and hydraulic properties (such as permeability of the buffer material and backfill material) change depending on the water chemistry. Task D was therefore a challenging Task focused on not only the relatively simple THM behaviour but also complex THM behaviour including chemical processes. Six research teams (BGR, CAS, JAEA, KAERI, SNL and Taipower) participated the Task D. BGR, CAS, JAEA, KAERI and Taipower research teams selected a THM approach, while the SNL research team selected a TH approach. Step 1 involved the simulation of laboratory test results and was important to check the numerical codes developed by the research teams. Step 1 was divided into four sub steps. The simulation results through the Step 1 identified the parameters for simulation of the Step 2. Basic parameters of the materials (buffer material, backfill material, rock mass, concrete, sand) were provided by JAEA. Special parameters which research team needed were identified by back analysis of Step 1. Most notably the mechanical behaviour of swelling and displacement depended on the applied model (elastic model or elastoplastic model). Parameters such as Young’s modulus were found to need smaller values than characterised in the fundamental laboratory test results (Step 1-1, 1-2) for the elastic model. Although laboratory experiments are usually simple, test results contained some error. For example, if the saturation level is 100 % or higher, it should be considered an error. This situation was presented in the Step 1-3. A possible reason is that the buffer material is a mixture of bentonite and silica sand. When a specimen is cut to measure volume or weight, sand grains will affect the measurement data. In Step 2, boundary conditions such as temperature on the surface of the simulated overpack, heater power of the electrical heaters installed in the simulated overpack, injection pressure and inflow rate of the test water, were applied. The outer boundary conditions can be selected using measured data (injection pressure and inflow rate of the test water that is controlled by the injection systems installed in the sand layer around the buffer material and in the boundary between backfill material and concrete support). Since such measured data has some noise, research teams developed their own simplified boundary conditions. Inner boundary conditions can be selected using measured data as heater power and temperature on the surface of the simulated overpack. These data also contain some noise, so research teams developed their own simplified developed boundary conditions. Task D validated various approaches thorough the simulation of the in-situ full scale EBS system including backfill of the gallery: variations in the coupling processes (THM or THC), analysis codes, and boundary conditions. Temperature distribution in the buffer material was simulated well by all research teams. This means thermal behaviour is not sensitive to the simulation approaches. Although the water content distribution on the outside of the buffer material was well simulated by all research teams, the simulation results differ from the measured values inside the buffer material (at the centre and inside, near the simulated overpack). The buffer material is made from tap water, but in the in-situ experiment, saline groundwater infiltrates the buffer material. Therefore, the selection of the hydraulic parameters of the buffer material greatly affects the simulation results of the re saturation behaviour of the buffer material. In the Horonobe EBS experiment, measured values suitable for validating the simulation results were not obtained near the simulated overpack. When simulating the pressure and deformation of the buffer material, the measurement data is easily affected by the installation conditions of the measurement sensors, so verifying the measurement data itself remains an issue. Mechanical simulation results differ depending on whether they are considered as elastic or elastoplastic phenomena. The accuracy of measured in-situ data can be assessed by detailed analysis comparing sampling specimen analysis and measured data. The Horonobe EBS experiment is scheduled to be dismantled in the future (FY2026 and 2027). This detailed dismantling investigation will finally confirm the measured data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

MPC-based double-layer real-time conditional cSelf-restoration for interconnected microgrids

In this report, we propose a novel model predictive control(MPC)-based real-time conditional self-restoration energy management system (CSR-EMS) for interconnected microgrids (IMGs) integrated with renewable energy sources (RESs) and energy storage systems (ESSs). Superior to the existing IMG self-restoration methods, the “conditionality” of the proposed CSR-EMS can economically realize self-restoration and grid-assisted restoration during energy deficiency or faults, in both islanded and grid-connected modes. Cost minimization is implemented as the objective function to judge in real-time which restoration mode is economically preferred. The proposed CSR-EMS comprises two layers–the lower layer operates locally to eliminate electricity fluctuations created by RESs and ensure economic effectiveness within an MG, whereas the upper layer oversees the real-time operational status of the IMG system and determines power exchange among microgrids (MGs) during abnormalities. In detail, when a microgrid inside the IMG system experiences an energy deficiency, the CSR-EMS, on an MPC basis, intelligently optimizes power production from each dispatchable distributed generator (DG), ESS, power imported from the main grid, and power exchange among the IMGs to maintain the demand–supply balance, while considering system recovery cost, state of charge (SoC) of ESSs and operation modes of the IMGs (i.e., grid-connected or islanded mode). Simulation results and comparisons with existing IMG self-healing EMSs demonstrate the economic efficacy of the proposed CSR-EMS strategy during normal and abnormal operations, which can be used as an energy control framework for modern power systems with multiple interconnected microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Examining the Impacts of Great Lakes Temperature Perturbations on Simulated Precipitation in the Northeastern United States

Most inland water bodies are not resolved by general circulation models, requiring that lake surface temperatures be estimated. Given the large spatial and temporal variability of the surface temperatures of the North American Great Lakes, such estimations can introduce errors when used as lower boundary conditions for dynamical downscaling. Lake surface temperatures (LSTs) influence moisture and heat fluxes, thus impacting precipitation within the immediate region and potentially in regions downwind of the lakes. For this study, the Advanced Research version of the Weather Research and Forecasting Model (WRF-ARW) was used to simulate precipitation over the six New England states during a 5-yr historical period. The model simulation was repeated with perturbed LSTs, ranging from 10°C below to 10°C above baseline values obtained from reanalysis data, to determine whether the inclusion of erroneous LST values has an impact on simulated precipitation and synoptic-scale features. Results show that simulated precipitation in New England is statistically correlated with LST perturbations, but this region falls on a wet–dry line of a larger bimodal distribution. Wetter conditions occur to the north and drier conditions occur to the south with increasing LSTs, particularly during the warm season. Additionally, the precipitation differences coincide with large-scale anomalous temperature, pressure, and moisture patterns. Care must therefore be taken to ensure reasonably accurate Great Lakes surface temperatures when simulating precipitation, especially in southeastern Canada, Maine, and the mid-Atlantic region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

THE GALAXY-HALO/SUBHALO CONNECTION: MASS RELATIONS AND IMPLICATIONS FOR SOME SATELLITE OCCUPATIONAL DISTRIBUTIONS

We infer the local stellar-to-halo/subhalo mass relations (MRs) for central and satellite galaxies separately. Our statistical method is an extension of the abundance matching, halo occupation distribution, and conditional stellar mass function formalisms. We constrain the model using several combinations of observational data, consisting of the total galaxy stellar mass function (GSMF), its decomposition into centrals and satellites, and the projected two-point correlation functions (2PCFs) measured in different stellar mass (M{sub *}) bins. In addition, we use the {Lambda}CDM halo and subhalo mass functions. The differences among the resulting MRs are within the model-fit uncertainties (which are very small, smaller than the intrinsic scatter between galaxy and halo mass), no matter what combination of data are used. This shows that matching abundances or occupational numbers is equivalent, and that the GSMFs and 2PCFs are tightly connected. We also constrain the values of the intrinsic scatter around the central-halo (CH) and satellite-subhalo (SS) MRs assuming them to be constant: {sigma}{sub c} = 0.168 {+-} 0.051 dex and {sigma}{sub s} = 0.172 {+-} 0.057 dex, respectively. The CH and SS MRs are actually different, in particular when we take the subhalo mass at the present-day epoch instead of at their accretion time. When using the MRs for studying the satellite population (e.g., in the Milky Way, MW), the SS MR should be chosen instead of the average one. Our model allows one to calculate several population statistics. We find that the central galaxy M{sub *} is not on average within the mass distribution of the most massive satellite, even for cluster-sized halos, i.e., centrals are not a mere realization of the high end of the satellite mass function; however for >3 Multiplication-Sign 10{sup 13} M{sub Sun} halos, {approx}15% of centrals could be. We also find that the probabilities of MW-sized halos of having N Magellanic Cloud (MC) sized satellites agree well with observational measures; for a halo mass of 2 Multiplication-Sign 10{sup 12} M{sub Sun }, the probability to have two MCs is 5.4%, but if we exclude those systems with satellites larger than the MCs, then the probability decreases to <2.2%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

Integrated Radiation Transport and Thermo-Mechanics Simulation of a PWR Assembly

The Advanced Multi-Physics (AMP) Nuclear Fuel Performance code (AMPFuel) is focused on predicting the temperature and strain within a nuclear fuel assembly to evaluate the performance and safety of existing and advanced nuclear fuel bundles within existing and advanced nuclear reactors. AMPFuel was extended to include an integrated nuclear fuel assembly capability for (one-way) coupled radiation transport and nuclear fuel assembly thermo-mechanics. This capability is the initial step towards incorporating an improved predictive nuclear fuel assembly modeling capability to accurately account for source terms, such as the neutron flux distribution, coolant conditions, and assembly mechanical stresses, of traditional (single-pin) nuclear fuel performance simulation. AMPFuel was used to model an entire 17 x 17 Pressurized Water Reactor (PWR) fuel assembly with many of the features resolved in three dimensions (for thermo-mechanics and/or neutronics), including the fuel, gap, and cladding of each of the 264 fuel pins, the 25 guide tubes, top and bottom structural regions, and the upper and lower (neutron) reflector regions. The final full-assembly calculation was executed on Jaguar (Cray XT5) at the Oak Ridge Leadership Computing Facility using 40,000 cores in under 10 hours to model over 162 billion degrees of freedom for 10 loading steps.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

134 billion intersecting brane models

The landscape of string vacua is very large, but generally expected to be finite in size. Enumerating the number and properties of the vacua is an important task for both the landscape and the swampland, in part to gain a deeper understanding of what is possible and “generic”. We obtain an exact counting of distinct intersecting brane vacua of type IIA string theory on the T 6 /Z 2 × Z 2 orientifold. Care is taken to only count gauge-inequivalent brane configurations. Leveraging the recursive nature by which branes may be added together one-by-one, we use dynamic programming to efficiently count the number of solutions of the tadpole, K-theory and supersymmetry consistency conditions. The distributions of 4D gauge group rank and complex structure moduli for the entire ensemble of intersecting brane vacua are presented. The methods we developed here may be useful in obtaining sharp upper and lower bounds on other corners of the landscape.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Adaptive approximation of higher order posterior statistics

Filtering is an approach for incorporating observed data into time-evolving systems. Instead of a family of Dirac delta masses that is widely used in Monte Carlo methods, we here use the Wiener chaos expansion for the parametrization of the conditioned probability distribution to solve the nonlinear filtering problem. The Wiener chaos expansion is not the best method for uncertainty propagation without observations. Nevertheless, the projection of the system variables in a fixed polynomial basis spanning the probability space might be a competitive representation in the presence of relatively frequent observations because the Wiener chaos approach not only leads to an accurate and efficient prediction for short time uncertainty quantification, but it also allows to apply several data assimilation methods that can be used to yield a better approximate filtering solution. The aim of the present paper is to investigate this hypothesis. We answer in the affirmative for the (stochastic) Lorenz-63 system based on numerical simulations in which the uncertainty quantification method and the data assimilation method are adaptively selected by whether the dynamics is driven by Brownian motion and the near-Gaussianity of the measure to be updated, respectively.

97 MATHEMATICS AND COMPUTING↗