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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Addressing Uncertainty in MultiSector Dynamics Research

MultiSector Dynamics (MSD) research explores the dynamics and co-evolutionary pathways of human and Earth systems and the emerging interdependent sectors of energy, water, agriculture, and transportation among others. The interactions between these sectors are central to MSD science, as they capture how processes and feedbacks across Earth, environmental, infrastructure, and societal systems shape transitions, socioeconomic risks, and the provision of services. By definition, MSD research requires deep integration across diverse scientific disciplines, ranging from the natural to the social sciences and engineering. All these disciplines apply a variety of numerical simulation models to study and understand their underlying systems of focus. The utility of these models hinges on the fidelity with which they represent the real systems and their ability to produce novel insights about systems and their interactions. The coupled human-natural systems typically represented are shaped by a multitude of interdependent human and natural processes which, when modeled, translate to highly complex, non-linear, interacting behaviors. This ever-increasing complexity massively expands the uncertainty space of a model and can be found in model inputs, processes and parameters. This is further amplified when several models are combined to answer multisectoral questions, as additional uncertainty regarding coupling relationships and interactions is introduced.

IM3, Uncertainty and Sensitivity Analysis, multise↗
DOE OSTI2023

Plutonium Age Dating Interlaboratory Comparison Overview - Project Design, Sample Preparation, and Results [Slides]

Project Design – How do you validate measured Pu model age? There are no certified reference materials (CRMs) that are certified for Pu model age or purification dates. There are no Am isotopic CRMs - IRMM 0243 243 Am spike has 241 Am impurity that can be used; Community working toward "consensus ages." This project executed and evaluated results from a Pu age dating interlaboratory comparison with six IAEA NWAL participant laboratories. It also ran the first quality control evaluation of single-picogram to sub-picogram scale interlaboratory 241 Am assay measurements from cotton swipe matrices. Results are promising, with a majority of 241 Am/ 241 Pu model age results agree to within 1 to 4 years. The calculated 241 Am assay results show interlaboratory variability, expanded percent uncertainties on calculated consensus 241 Am concentrations were: PuAge-S1 = 3.1 %, PuAge-S2 = 23 %, and PuAge-S3 = 26 %. Data can be used to investigate laboratory methods and improve precision and accuracy of 241 Pu and 241 Am assay for future campaigns.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

The impact of neutrino-nucleus interaction modeling on new physics searches

Accurate neutrino-nucleus interaction modeling is an essential requirement for the success of the accelerator-based neutrino program. As no satisfactory description of cross sections exists, experiments tune neutrino-nucleus interactions to data to mitigate mis-modeling. In this work, we study how the interplay between near detector tuning and cross section mis-modeling affects new physics searches. We perform a realistic simulation of neutrino events and closely follow NOvA’s tuning, the first published of such procedures in a neutrino experiment. We analyze two illustrative new physics scenarios, sterile neutrinos and light neutrinophilic scalars, presenting the relevant experimental signatures and the sensitivity regions with and without tuning. While the tuning does not wash out sterile neutrino oscillation patterns, cross section mis-modeling can bias the experimental sensitivity. In the case of light neutrinophilic scalars, variations in cross section models completely dominate the sensitivity regardless of any tuning. Our findings reveal the critical need to improve our theoretical understanding of neutrino-nucleus interactions, and to estimate the impact of tuning on new physics searches. We urge neutrino experiments to follow NOvA’s example and publish the details of their tuning procedure, and to develop strategies to more robustly account for cross section uncertainties, which will expand the scope of their physics program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Vapor and Liquid ( p –ρ– T–x ) Measurements of Binary Refrigerant Blends Containing R-32, R-152a, R-227ea, R-1234yf, and R-1234ze(E)

In this article, The pressure–density–temperature–composition (p–ρ–T–x) data of binary refrigerant mixtures containing R-32 (difluoromethane), R-152a (1,1,-difluoroethane), R-227ea (1,1,1,2,3,3,3-heptafluoropropane), R-1234yf (2,3,3,3-tetrafluoropropene), and R-1234ze(E) (trans-1,3,3,3-tetrafluoropropene) were measured in both the vapor and liquid phases using a two-sinker, magnetic suspension densimeter. The specific samples in this study comprised two compositions of approximately (0.3/0.7) and (0.7/0.3) mole fraction for each of the following four binary refrigerant blends: R-32 + R-1234yf, R-32 + R-1234ze(E), R-1234yf + R-152a, and R-1234ze(E) + R-227ea. Single-phase vapor densities were measured over a temperature range of approximately 253 to 293 K and pressures from 0.05 to 0.98 MPa. Single-phase liquid and supercritical densities were measured over a temperature range of approximately 230 to 400 K and pressures up to 22 MPa; for refrigerant blends containing R-1234yf, the maximum pressure was limited to 14 MPa. Overall relative combined, expanded (k = 2) uncertainties in density ranged from 0.025 to 0.191%, with an average uncertainty of approximately 0.05%. Here, we present measurement results, along with comparisons to available literature data and to default equations of state and mixture models included in REFPROP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Extension of charged-particle spectrometer capabilities for diagnosing implosions on OMEGA, Z, and the NIF

New designs and a new analysis technique have been developed for an existing compact charged-particle spectrometer on the NIF and OMEGA. The new analysis technique extends the capabilities of this diagnostic to measure arbitrarily shaped ion spectra down to 1 MeV with yields as low as 10 6 . Three different designs are provided optimized for the measurement of DD protons, T 3 He deuterons, and 3 He 3 He protons. The designs are highly customizable, and a generalized framework is provided for optimizing the design for alternative applications. Additionally, the understanding of the detector’s response and uncertainties is greatly expanded upon. A new calibration procedure is also developed to increase the precision of the measurements.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Veridical data science

Building and expanding on principles of statistics, machine learning, and scientific inquiry, we propose the predictability, computability, and stability (PCS) framework for veridical data science. Our framework, composed of both a workflow and documentation, aims to provide responsible, reliable, reproducible, and transparent results across the data science life cycle. The PCS workflow uses predictability as a reality check and considers the importance of computation in data collection/storage and algorithm design. It augments predictability and computability with an overarching stability principle. Stability expands on statistical uncertainty considerations to assess how human judgment calls impact data results through data and model/algorithm perturbations. As part of the PCS workflow, we develop PCS inference procedures, namely PCS perturbation intervals and PCS hypothesis testing, to investigate the stability of data results relative to problem formulation, data cleaning, modeling decisions, and interpretations. We illustrate PCS inference through neuroscience and genomics projects of our own and others. Moreover, we demonstrate its favorable performance over existing methods in terms of receiver operating characteristic (ROC) curves in high-dimensional, sparse linear model simulations, including a wide range of misspecified models. Finally, we propose PCS documentation based on R Markdown or Jupyter Notebook, with publicly available, reproducible codes and narratives to back up human choices made throughout an analysis. The PCS workflow and documentation are demonstrated in a genomics case study available on Zenodo.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Autonomous RPOD for Arbitrarily Configured Spacecraft with Anomaly Detection

Autonomous GN&C is a necessary component for a sustainable deep-space logistics architecture. The challenges for establishing robust autonomy are numerous, from state uncertainty, to anomaly detection and recovery. In this work, previous work investigating autonomous GN&C for arbitrary thruster configurations and mass properties is expanded to include state uncertainty and anomaly detection. Logistics vehicles with off-center-of-mass thruster configurations and in the presence of large but realistic state uncertainties are simulated in a Rendezvous, Proximity Operations and Docking scenario. Furthermore, stuck and non-functional thrusters are simulated, demonstrating the vehicle's ability to identify and overcome thruster anomalies. The simulations demonstrate that even with these realistic ambiguities, the vehicle is able to converge to the desired pose.

GN&C↗
DOE OSTI2021

Material Interactions in Severe Accidents – Benchmarking the MELCOR V2.2 Eutectics Model for a BWR-3 Mark-I Station Blackout: Part II – Uncertainty Analysis

Single case comparisons between severe accident simulations can provide detailed insights into severe accident model behavior, however, they cannot offer insights into model uncertainty, sensitivity to uncertain parameters, or underlying model biases.Here in this analysis, the single case benchmark comparison of the MELCOR material interaction models for a station blackout (SBO) scenario of a boiling water reactor (BWR) using representative Fukushima Daiichi Unit 1 boundary conditions is expanded to include an uncertainty analysis. As part of this uncertainty analysis, 1200 simulations are performed for each material interaction model (2400 total), with random sampling of 14 uncertain MELCOR input parameters. Input parameters are selected for their impact on models representing core degradation processes. These include candling, fuel rod failure, debris quenching and dryout. The analysis performed here is not a traditional “best-estimate” uncertainty analysis that uses best-estimate parameters or identifies best-estimate figure of merit distributions. Instead, it is an exploratory uncertainty analysis that identifies and interrogates underlying model form biases of the two material interaction models (eutectics and interactive materials models). Uniform distributions are applied to all uncertain parameters to ensure coverage of the model parameter uncertainty space. Key findings from this study include underlying model form biases exhibited by material interaction models, and notable differences in accident progression outcomes between the material interaction models. This uncertainty study extends and confirms the conclusions from the first part of this study, which compared the impact of material interaction modeling on simulation of a short-term station blackout scenario with representative Fukushima Daiichi Unit I boundary conditions. In particular, this study confirms that the eutectics model generally exhibits accelerated degradation and failure of fuel components, the core plate, and the lower head. The eutectics model also has a tendency to exhibit a greater degree of core degradation, greater debris mass formation, and larger debris mass ejection. Finally, the eutectics model exhibits higher maximum temperatures for fuel, cladding, particulate debris, oxidic molten pool, and metallic molten pool components than the interactive materials model; interactive materials model simulations exhibit a soft “limitation” on maximum temperatures that is related to the temperature at which material relocation occurs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

The Universe at z > 10: predictions for JWST from the universemachine DR1

The James Webb Space Telescope (JWST) is expected to observe galaxies at z > 10 that are presently inaccessible. Here, we use a self-consistent empirical model, the universemachine, to generate mock galaxy catalogues and light-cones over the redshift range z = 0-15. These data include realistic galaxy properties (stellar masses, star formation rates, and UV luminosities), galaxy–halo relationships, and galaxy–galaxy clustering. Mock observables are also provided for different model parameters spanning observational uncertainties at z < 10. We predict that Cycle 1 JWST surveys will very likely detect galaxies with M* > 10 7 M⊙ and/or M 1500 < -17 out to at least z ~ 13.5. Number density uncertainties at z > 12 expand dramatically, so efforts to detect z > 12 galaxies will provide the most valuable constraints on galaxy formation models. Additionally, the faint-end slopes of the stellar mass/luminosity functions at a given mass/luminosity threshold steepen as redshift increases. This is because observable galaxies are hosted by haloes in the exponentially falling regime of the halo mass function at high redshifts. Hence, these faint-end slopes are robustly predicted to become shallower below current observable limits (M* < 10 7 M⊙ or M 1500 > -17). For reionization models, extrapolating luminosity functions with a constant faint-end slope from M 1500 = -17 down to M 1500 = -12 gives the most reasonable upper limit for the total UV luminosity and cosmic star formation rate up to z ~ 12. We compare to three other empirical models and one semi-analytic model, showing that the range of predicted observables from our approach encompasses predictions from other techniques. Public catalogues and light-cones for common fields are available online.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Speed of Sound Measurements of Binary Mixtures of Hydrofluorocarbons [Pentafluoroethane (R-125), 1,1-Difluoroethane (R-152a), or 1,1,1,2,3,3,3-Heptafluoropropane (R-227ea)] with Hydrofluoroolefins [2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E))]

In this article, speed of sound data measured using a dual-path pulse-echo instrument are reported for three binary refrigerant mixtures, R-125/1234yf, R-1234yf/152a, and R-1234ze(E)/227ea, at compositions of (0.33/0.67) and (0.67/0.33) mole fraction. The speed of sound was studied at temperatures ranging from 230 K to 345 K from pressures slightly above the bubble point curve up to 20 MPa for the mixtures containing R-1234yf and 49 MPa for the R-1234ze(E)/227ea mixtures. The relative combined expanded speed of sound uncertainty ranged from 0.039 % to 0.317 % with a mean uncertainty over all state points of less than 0.10 %. The reported data are compared to the most recent mixture models in REFPROP for each blend studied. Comparisons of available mixture models for the R-125/1234yf and R-1234yf/152a blends exhibit average absolute deviation values ranging from 0.10 % to 0.27 %, and the average absolute deviations for R-1234ze(E)/227ea blends range from 0.62 % to 0.94 %. The comparisons show that only minor adjustments are required to the R-125/1234yf and R-1234yf/152a mixture models to represent the speed of sound data within its uncertainty. However, significant adjustments are needed to improve the current mixture models for the R-1234ze(E)/227ea blend. Deficiencies with the R-1234ze(E)/227ea mixture model are not unexpected since it (1) utilizes a pure-fluid EOS R-1234ze(E) that has been shown to inaccurately represent R-1234ze(E) speed of sound values and (2) uses binary interaction parameters for the chemically similar mixture of R-1234yf/227ea.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Compressed Liquid (${{p}}$-${{\rho}}$-${{T}}$) Measurements of trans-1,2-Dichloroethene [R-1130(E)]

Pressure-density-temperature (${{p}}$-${{\rho}}$-${{T}}$) data for the refrigerant R-1130(E) (trans-1,2-dichloroethene) were measured in the compressed liquid phase using an automated vibrating-tube densimeter. Overall, the measurements covered temperatures from 270 K to 410 K and pressures from 0.5 MPa to 30 MPa. Relative combined, expanded (95% confidence level) uncertainties ranged from approximately 0.05% to 0.06%. Here, we present measurement results, along with comparisons to available literature data and to a generalized extended corresponding states model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Safety-Related Instrumentation and Control Pilot Upgrade: Initial Scoping Phase Implementation and Lessons Learned

In May 2016, the U.S. Nuclear Regulatory Commission (NRC) staff provided a digital instrumentation and control (I&C) regulatory infrastructure integrated action plan to the NRC for approval. One of the objectives of that plan was to establish a clear regulatory structure with reduced regulatory uncertainty to enable the expanded safe use of digital I&C in commercial nuclear reactors while continuing to ensure safety and security. To achieve this end, the NRC, with collaboration from industry, developed a streamlined License Amendment Request Alternate Review (AR) process for safety-related (SR) digital I&C upgrades. In spite of this effort, the industry has remained reluctant to perform such I&C upgrades because of perceived regulatory and financial risks associated with being the first or an early adopter of the AR process for SR I&C upgrades. The U.S. Department of Energy Light Water Reactor Sustainability Program at the Idaho National Laboratory performed Initial Scoping Phase research to help break this impasse by supporting a SR I&C Pilot Upgrade, working with MPR Associates, ScottMadden Inc., and Exelon Generation. Exelon’s Limerick Generating Station (LGS) was selected as the target for this research. This paper summarizes the Initial Scoping Phase engineering and operations, licensing, and project management activities necessary to bound the scope, schedule, and estimated cost of the project sufficiently to enable utility management authorization of Conceptual Design Phase activities. These efforts and associated products are intended to provide a template to support larger industry efforts to perform similar upgrades as a foundation stone for a digital transformation that will improve plant safety, reliability, and operational performance while lowering plant total cost of ownership. As a result of the combined effort of Exelon Generation and research participants, Conceptual Design Phase activities for the subject upgrade at LGS were approved by Exelon. Further, the U.S. Department of Energy also awarded a $50 million cost share award to Exelon in order to pave the way for SR I&C modernization and associated control room upgrades across the U.S. nuclear fleet. Additional research reports are planned for the Conceptual Design Phase, Detailed Design Phase, and the Implementation Phase of the LGS project to document the process followed and promulgate lessons learned to industry.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Enhancing generative molecular design via uncertainty-guided fine-tuning of variational autoencoders

In recent years, deep generative models have been successfully applied to various molecular design tasks, particularly in the life and materials sciences. One critical challenge for pre-trained generative molecular design (GMD) models is to fine-tune them to be better suited for downstream design tasks that aim at optimizing specific molecular properties. However, redesigning and training an existing effective generative model from scratch for each new design task are impractical. Furthermore, the black-box nature of typical downstream tasks that involve property prediction makes it nontrivial to optimize the generative model in a task-specific manner. In this work, we propose an uncertainty-guided fine-tuning strategy that can effectively enhance a pre-trained variational autoencoder (VAE) for GMD through performance feedback in an active learning setting. The strategy begins by quantifying the model uncertainty of the generative model using an efficient active subspace-based UQ (uncertainty quantification) scheme. Next, the decoder diversity within the characterized model uncertainty class is explored to expand the viable space of molecular generation. The low-dimensionality of the active subspace makes this exploration tractable using a black-box optimization scheme, which in turn enables us to identify and leverage a diverse set of high-performing models to generate enhanced molecules. Empirical results across six target molecular properties using multiple VAE-based generative models demonstrate that our uncertainty-guided fine-tuning strategy consistently leads to improved models that outperform the original pre-trained models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Opportunities and challenges for the expansion of LFP battery supply chains

Global markets for energy storage are growing rapidly, with some applications transitioning from traditional LiNi x Mn y Co 1−x−y O 2 (NMC) toward LiFePO 4 (LFP) due to cost, safety, and performance advantages. Battery growth has seeded interest in critical material supplies such as high-purity lithium precursors. In contrast, challenges in securing high-purity iron and phosphorus, historically not considered critical materials, are often overlooked. Precursors must remain inexpensive to maintain LFP's current cost advantage, which leverages the low-cost (∼$\$100$ per t) FeSO 4 byproduct from titanium dioxide manufacturing and will not be available as LFP manufacturing expands. As an alternative, iron is mined primarily for steel manufacturing, for which the existing supply chain and beneficiation process is optimized. LFP batteries require small iron volumes compared to steel (0.11%), but profit margins associated with existing low-cost iron ores and high costs (∼$27 000 per t) associated with low volume high-purity iron oxides may limit interest in manufacturing small volumes of high-purity, specialized iron battery precursors. The complementary LFP precursor, phosphoric acid (H 3 PO 4 ), is primarily utilized in fertilizers. Of the current phosphate ore demand for fertilizers, 4–22.8% would be required to meet projected 2045 LFP H 3 PO 4 demand, suggesting significant supply chain planning is needed to achieve projected demand. If only higher-grade material is considered, demand jumps to 15–77% of current world production. While lithium precursor purity requirements have been evaluated (Li 2 CO 3 is commonly defined as ≥99.5%), “battery grade” iron and phosphorus precursors remain poorly defined, with no internationally accessible and widely adopted standard, further challenging expanding industry by creating manufacturing uncertainty and increasing potential costs.

25 ENERGY STORAGE↗
DOE OSTI2021

Differential analysis of incompressibility in neutron-rich nuclei

Both the incompressibility K A of a finite nucleus of mass A and that (K ∞ ) of infinite nuclear matter are fundamentally important for many critical issues in nuclear physics and astrophysics. While some consensus has been reached about K ∞ , accurate theoretical predictions and experimental extractions of K τ characterizing the isospin dependence of K A have been very difficult. We propose a differential approach to extract K τ and K ∞ independently from the K A data of any two nuclei in a given isotope chain. Applying this method to the K A data from isoscalar giant monopole resonances (ISGMR) in even-even Pb, Sn, Cd, and Ca isotopes taken by Garg et al. at the Research Center for Nuclear Physics (RCNP), Osaka University, Japan, we find that the 106 Cd– 116 Cd and 112 Sn– 124 Sn pairs having the largest differences in isospin asymmetries in their respective isotope chains measured so far provide consistently the most accurate up-to-date K τ value of K τ = –616 ± 59 MeV and K τ =–623 ± 86 MeV, respectively, largely independent of the remaining uncertainties of the surface and Coulomb terms in expanding K A , while the K ∞ values extracted from different isotopes chains are all well within the current uncertainty range of the community consensus for K ∞ . Moreover, the size and origin of the “soft Sn puzzle” is studied with respect to the “stiff Pb phenomenon.” Furthermore, it is found that the latter is favored due to a much larger (by ≈ 380 MeV) K τ for Pb isotopes than for Sn isotopes, while K ∞ from analyzing the K A data of Sn isotopes is only about 5 MeV less than that from analyzing the Pb data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Measurement of non-prompt ${{\textrm{D}}^{0}}$-meson elliptic flow in Pb–Pb collisions at $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV

The elliptic flow (v 2 ) of D 0 mesons from beauty-hadron decays (non-prompt D 0 was measured in midcentral (30–50%) Pb–Pb collisions at a centre-of-mass energy per nucleon pair $\sqrt{s_{\textrm{NN}}} = 5.02$ TeV with the ALICE detector at the LHC. The D 0 mesons were reconstructed at midrapidity $(|y|<0.8)$ from their hadronic decay D 0 →$K^-\pi^+$, in the transverse momentum interval $2< p_{\textrm{T}} < 12$ GeV/c. The result indicates a positive v 2 for non-prompt D 0 mesons with a significance of 2.7σ. The non-prompt D 0 -meson v 2 is lower than that of prompt non-strange D mesons with 3.2σ significance in $2< p_\textrm{T} < 8~\textrm{GeV}/c$, and compatible with the v 2 of beauty-decay electrons. Theoretical calculations of beauty-quark transport in a hydrodynamically expanding medium describe the measurement within uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1984

Measuring planetary neutron albedo fluxes by remote gamma-ray sensing

In order to measure the planetary neutron albedo fluxes, a neutron-absorbing shield which emits gamma rays of characteristic energy and serves as a neutron detector, is added to a gamma-ray spectrometer (GRS). The gamma rays representing the neutron flux are observed against interference consisting of cosmic gamma rays, planetary continuum and line emission, and gamma rays arising from the interaction of cosmic rays with the GRS and the spacecraft. The uncertainty and minimum detection limits in neutron albedo fluxes are calculated for two missions, a lunar orbiter and a comet nucleus rendezvous. A GRS on a lunar orbiter at 100 km altitude detects a thermal neutron albedo flux as low as 0.002/sq cm/s and an expected flux of about 0.6/sq cm/s is measured with an uncertainty of 0.001/sq cm/s, for a 100 h observation period. For the comet nucleus, again in a 100 h observing period, a thermal neutron albedo flux is detected at a level of 0.006/sq cm/s and an expected flux of about 0.4/sq cm/s is measured with an uncertainty of 0.004/sq cm/s. The expanded geological capabilities made possible by this technique include improvements in H sensitivity, spatial resolution, and measurement depth; and an improved model of induced gamma-ray emission.

Haines, E. L.↗
NASA NTRSDate not supplied

A Practical Approach to Uncertainty Quantification Using Probability Boxes

To date, while the use of CFD for aerospace vehicle design and development is prevalent, the documentation of uncertainties associated with the simulations are rare. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the research and engineering design community, test and evaluation community, and ultimately certification for flight. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. These factors have prevented the adoption of UQ methods in the engineering design and development cycle. This presentation will outline a credible approach to UQ using Probability Boxes that is straightforward to apply, and can readily be automated using existing UQ tool sets such as the DAKOTA packaged developed at Sandia. The added expense incurred when moving away from a deterministic CFD process to a stochastic one that captures uncertainties to enable risk-informed decision making will be discussed, as well as effective ways to reduce the computational costs.

Uncertainty Quantification↗