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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 487 records · Page 27

A Hybrid Physics-Based, Data-Driven Approach to Model Damage Accumulation in Corrosion of Polymeric Adhesives

The degradation of polymeric adhesives in dissimilar joints is a menace to electric and structural components of the automotive industry. In polymeric adhesives, failure often occurs due to damage accumulated from discrete environmental sources—thermal degradation, oxidation, hydrolysis, radiation, and moisture—that are combined with progressive damage mechanisms, such as aging and fatigue. Because most damage mechanisms that lead to degradation act in parallel, the estimation of the lifetime of a polymeric material becomes a significant reliability issue, no study currently exists that can simultaneously consider even two of these phenomena. Most current efforts are directed toward a single-phenomenon, single-model approach in which a model is developed to cover one specific damage mechanism. While this approach is advantageous in exploring single mechanisms, it is strongly inconclusive for degradation that occurs by multiple damage mechanisms. Our team plans to take a fresh perspective by designing a hybrid constitutive/data-driven approach that allows models of different damage mechanisms to be integrated into one model and then used to explore the degradation-induced failure of polymeric adhesives. The theoretical-computational part of this work is divided into four research components as described in the Approach section below.

36 MATERIALS SCIENCE↗

A Surrogate-based Adaptive Sampling Approach for History Matching and Uncertainty Quantification

A critical procedure in reservoir simulations is history matching (or data assimilation in a broader sense), which calibrates model parameters such that the simulation results are consistent with field measurements, and hence improves the credibility of the predictions given by the simulations. Often there exist non-unique combinations of parameter values that all yield the simulation results matching the measurements. For such ill-posed history matching problems, Bayesian theorem provides a theoretical foundation to represent different solutions and to quantify the uncertainty with the posterior PDF. Lacking an analytical solution in most situations, the posterior PDF may be characterized with a sample of realizations, each representing a possible scenario. A novel sampling algorithm is presented here for the Bayesian solutions to history matching problems. We aim to deal with two commonly encountered issues: 1) as a result of the nonlinear input-output relationship in a reservoir model, the posterior distribution could be in a complex form, such as multimodal, which violates the Gaussian assumption required by most of the commonly used data assimilation approaches; 2) a typical sampling method requires intensive model evaluations and hence may cause unaffordable computational cost. In the developed algorithm, we use a Gaussian mixture model as the proposal distribution in the sampling process, which is simple but also flexible to approximate non-Gaussian distributions and is particularly efficient when the posterior is multimodal. Also, a Gaussian process is utilized as a surrogate model to speed up the sampling process. Furthermore, an iterative scheme of adaptive surrogate refinement and re-sampling ensures sampling accuracy while keeping the computational cost at a minimum level. The developed approach is demonstrated with an illustrative example and shows its capability in handling the above-mentioned issues. Multimodal posterior of the history matching problem is captured and are used to give a reliable production prediction with uncertainty quantification. The new algorithm reveals a great improvement in terms of computational efficiency comparing previously studied approaches for the sample problem.

Li, Weixuan↗

Assessing and Enabling Trustworthy Predictions for High-Consequence Decisions

Predictions from physics-based computational models provide critical information to inform high consequence decisions, e.g., engineering design decisions. The ability to assess the reliability of such predictions is therefore critical. However, to date, reliability assessment rely heavily on expert judgment and qualitative arguments. This report details the efforts of LDRD 233072 to develop quantitative methods to assess reliability of model predictions, especially in the context of simplifying assumptions that can impact their reliability.

42 ENGINEERING↗

An Assessment of Energy Potential at Non-Powered Dams in the United States

The United States has produced clean, renewable electricity from hydropower for more than 100 years, but hydropower-producing facilities represent only a fraction of the infrastructure development that has taken place on the nation’s waterways. In contrast to the roughly 2,500 dams that provide 78 gigawatts (GW) 1 of conventional and 22 GW of pumped-storage hydropower, the United States has more than 80,000 non-powered dams (NPDs)—dams that do not produce electricity—providing a variety of services ranging from water supply to inland navigation. Importantly, many of the monetary costs and environmental impacts of dam construction have already been incurred at NPDs, so adding power to the existing dam structure can often be achieved at lower cost, with less risk, and in a shorter timeframe than development requiring new dam construction. The abundance, cost, and environmental favorability of NPDs, combined with the reliability and predictability of hydropower, make these dams a highly attractive source for expanding the nation’s renewable energy supply. To better characterize this unique national resource, the U.S. Department of Energy (DOE) Wind and Water Power Program has undertaken a national-scale analysis of U.S. dams to determine the ability of NPDs to provide hydroelectric power. DOE’s Oak Ridge National Laboratory (ORNL), with input from DOE’s Idaho National Laboratory, quantified the potential capacity and generation available from adding power production capability to U.S. NPDs. Of the more than 80,000 NPDs throughout the U.S., 54,391 dams were analyzed, with remaining dams eliminated from consideration due to erroneous geographic information, or erroneous flow or drainage area attributes that could not be resolved and corrected through independent investigation of maps and records. Anecdotal information suggests that these dams with missing or erroneous information are likely to be relatively small or have low potential to produce hydroelectric energy. Dams with a reported height of less than five feet were also excluded from analysis. A thorough quality control and review process ensured that the 54,391 remaining NPDs were analyzed and characterized as accurately as possible. Figure ES-1 demonstrates the spatial and capacity potential distribution of the nation’s NPDs. Electric generating capacities included in the report were calculated using the assumption that all water passing a facility would be available for conversion into electrical energy and that hydraulic head at the facility would remain constant. The analysis did not consider the economic feasibility of developing each unpowered facility. The assessment provides preliminary information for stakeholders (such as developers, municipal planners, and policymakers), who can further evaluate the potential to increase hydropower production at NPD sites. Developers could use the information provided in this assessment to focus on more detailed analysis of sites that demonstrate a reasonable potential for being developed. Adding power to U.S. NPDs has the potential to add up to 12 GW (12,000 megawatts or MW) of new renewable capacity—a potential equivalent to increasing the size of the existing conventional hydropower fleet by 15%. A majority of this potential is concentrated in just 100 NPDs, which could contribute approximately 8 GW of clean, reliable hydropower; the top 10 facilities alone could add up to 3 GW of new hydropower. Eighty-one of the 100 top NPDs are U.S. Army Corps of Engineers (USACE) facilities, many of which, including all of the top 10, are navigation locks on the Ohio River, Mississippi River, Alabama River, and Arkansas River, as well as their major tributaries. This study also shows that dams owned by the U.S. Bureau of Reclamation hold the potential to add approximately 260 MW of capacity; the Bureau has also engaged in an effort to conduct a more detailed evaluation of its own facilities.

13 HYDRO ENERGY↗

Addressing an aging facility: improving reliability of the defense waste processing facility at the Savannah River Site - 15539

The High Level Waste program at the Savannah River Site significantly reduces environmental risks associated with the storage of radioactive waste from legacy efforts to separate fissionable nuclear material from irradiated targets and fuels. The Defense Waste Processing Facility treats and immobilizes High Level Waste into a durable borosilicate glass for safe, permanent storage. Construction of the facility began in 1983 and radioactive operations commenced in 1996. In an effort to support the disposition of radioactive waste and accelerate tank closure for the balance of the Savannah River Site mission, the Defense Waste Processing Facility recently underwent an extensive reliability review in 2013 to understand future needs as well as to address aging infrastructure. As a product of this review, a Performance Improvement Plan was developed to systematically address three major focus areas including, a) asset preservation, b) facility housekeeping, and 3) process improvements. Since issuance of the plan, significant progress has been made in each of these areas to improve the reliability and predictability of the Defense Waste Processing Facility. Providing consistent, constructive, and concise communications is vital in the face of a changing budgetary environment. The Savannah River Site case study provides an example of the U.S. Department of Energy - Savannah River (DOE-SR) and SRR partnering to inform stakeholders about cleanup progress at the site. DOE-SR and SRR periodically and consistently provide both annual written progress reports under the Federal Facility Agreement and quarterly written progress reports under the landfill permit to the government regulators. Through the Liquid Waste System Plans, DOE-SR and SRR constructively and concisely summarize both the significant progress made and explain how a changed budget can impact the goals moving forward. Furthermore, DOE-SR and SRR informs the community and general public about the Site's progress and future during Citizens Advisory Board meetings. In addition, through the new proposed model for complex-wide communications, stakeholders can better understand how budget constraints will affect them. The set-aside program would also encourage stakeholder participation and involvement in helping each state and site obtain extra funding through performance evaluations. Waste management organizations can benefit in a number of ways from an effective partnership approach to communicate with stakeholders about available funding. Keeping an open and honest dialogue with regulatory agencies can help preserve confidence, thus mitigating or completely avoiding costly and distracting fines and penalties. Informing the public not only promotes trust, but also spurs the public to exercise its right to demand more information and voice any concerns to elected or DOE officials. With this approach, DOE can receive better understanding and cooperation from stakeholders in a changing budgetary landscape. Furthermore, a set-aside competitive program would encourage efficiency and innovation that could lead to further cost savings for the government while providing extra funding for cleanup efforts. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fundamental Vibrational Analyses of the HCN Monomer, Dimer and Associated Isotopologues

In this work we provide high level ab initio treatments of the structures, vibrational frequencies, and electronic energies of the HCN monomer and dimer systems along with several isotopologues. Additionally, the plethora of information related to this system within the literature is summarized and serves as a basis for comparison with the results of this paper. The geometry of the dimer and monomer are reported at the all electroncoupled-cluster singles, doubles, and perturbative triples level of theory [AE-CCSD(T)] with the correlation consistent quadruple-zeta quality basis sets with extra core functions (cc-pCVQZ) from Dunning. The theoretical geometries and electronic structures are further analyzed through the use of the Natural Bond Orbital (NBO) method and Natural Resonance Theory (NRT). At the AE-CCSD(T)/cc-pCVQZ level of theory, the full cubic with semi-diagonal quartic force field for nine dimer and four monomer isotopologues (the parent isotopologue along with 15N, 13C, and D derivatives) were obtained to treat the anharmonicity of the vibrations via second order vibrational perturbation theory (VPT2). Lastly, the enthalpy change associated with the formation of the dimer from two monomer units was determined using the focal point analysis. Computations including coupled-cluster through perturbative quadruples as well as basis sets up to six-zeta quality, including core functions (cc-pCVXZ, X=D,T,Q,5,6) were used to extrapolate to the AE-CCSDT(Q)/CBS energy associated with this hydrogen-bond forming process. After appending anharmonic zero-point vibrational, relativistic, and diagonal Born-Oppenheimer corrections, we report a value of -3.93 kcal mol -1 for the enthalpy of formation. To our knowledge, each set of results (geometries, vibrational frequencies, and energetics) reported in this study represents the highest-level and most reliable theoretical predictions reported for this system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Resummation for lattice QCD calculation of generalized parton distributions at nonzero skewness

Large-momentum effective theory (LaMET) provides an approach to directly calculate the x-dependence of generalized parton distributions (GPDs) on a Euclidean lattice through power expansion and a perturbative matching. When a parton’s momentum becomes soft, the corresponding logarithms in the matching kernel become non-negligible at higher orders of perturbation theory, which requires a resummation. But the resummation for the off-forward matrix elements at nonzero skewness ξ is difficult due to their multi-scale nature. In this work, we demonstrate that these logarithms are important only in the threshold limit, and derive the threshold factorization formula for the quasi-GPDs in LaMET. We then propose an approach to resum all the large logarithms based on the threshold factorization, which is implemented on a GPD model. We demonstrate that the LaMET prediction is reliable for [−1 + x 0 , −ξ − x 0 ] ∪ [−ξ + x 0 , ξ − x 0 ] ∪ [ξ + x 0 , 1 − x 0 ], where x 0 is a cutoff depending on hard parton momenta. Through our numerical tests with the GPD model, we demonstrate that our method is self-consistent and that the inverse matching does not spread the nonperturbative effects or power corrections to the perturbatively calculable regions.

hadronic spectroscopy↗

Circulating CD16+CD56+ nature killer cells indicate the prognosis of colorectal cancer after initial chemotherapy

As the prognosis of colorectal cancer (CRC) does not always coincide with the pathology and/or surgical findings, a reliable noninvasive prediction tool for the prognosis of CRC is needed. Patients admitted for initial treatment of CRC between January 1, 2015 and December 31, 2015 were retrieved and reviewed. Records of circulating CD16+ CD56+ natural killer (NK) cells were analyzed before and after the initial chemotherapy of FOLFOX plan. Patients were followed up until June 30, 2019. One hundred and twenty-four cases after the FOLFOX chemotherapy were enrolled into this study. There were no significant differences in gender, age, or number of metastasis cases between the survival group and the nonsurvival group (p > 0.05), but significant differences in pre-chemotherapy, post-chemotherapy, and the differences between pre- and post-chemotherapy circulating CD16+ CD56+ NK cells between the survival group and the nonsurvival group (p < 0.01, p < 0.01, and p < 0.05, respectively) were observed. For the prediction of survival and nonsurvival CRC cases, the Areas Under the Curve were 0.626 and 0.759 in the Receiver-Operating Characteristic curves for the pre- and post-chemotherapy circulating CD16+ CD56+NK cells, respectively. Using an optimal cutoff value of 11.8% in post-chemotherapy circulating CD16+CD56+NK cells to differentiate survival and nonsurvival cases, the odds ratio was 0.12 (0.05, 0.27), p < 0.001. The percentages of both pre-chemotherapy and post-chemotherapy circulating CD16+CD56+NK cells were negatively correlated with the prognosis of CRC. The percentage of post-chemotherapy circulating CD16+CD56+NK cells was able to effectively predict the prognosis of CRC cases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Homogenization of Al x CoCrFeNi high-entropy alloys with improved corrosion resistance

The present work investigates the homogenization effect of 1250 °C heat treatment on the Al x CoCrFeNi high-entropy alloys (HEAs). The multi-phase microstructures with chemical segregations are inevitable with the increased Al content in the alloys, which cause work function variations and localized corrosion. After heat treatment, the homogenization effect revealed by the microstructure simplification and chemical-segregation reduction leads to the decreased work function variations and the improved corrosion resistance. Furthermore, thermodynamic calculations that are reliable to predict the phase transformations of the Al x CoCrFeNi HEAs, indicates a further enhancement in corrosion resistance through annealing could be guided for many other HEAs systems.

36 MATERIALS SCIENCE↗

Distributed renewable energy resource trust metrics and secure routing

To ensure reliable and predictable service in the electrical grid between distributed renewable distributed energy resources (DERs) it is important to gauge the level of trust present within critical components and DER aggregators (DERAs). Although trust throughout a smart grid is temporal and dynamically varies according to measured states, it is possible to accurately formulate communications and service level strategies based on such trust measurements. Utilizing an effective set of machine learning and statistical methods, it is shown that establishment of trust levels between DERAs using behavioral pattern analysis is possible. Further, it is also shown that the establishment of such trust can facilitate simple secure communications routing between DERAs. Providing secure routing between DERAs enables a grid operator to maintain service level agreements to its customers, reduce the attack surface and increase operational resiliency.

97 MATHEMATICS AND COMPUTING↗

Time-resolved spray characterization via unified optical flow and binarization technique

This work leverages an unsupervised machine learning and advanced image processing techniques to characterize the breakup of fuel sprays in a small-scale combustor under reacting conditions, providing valuable insights into near-nozzle flow phenomenology. The proposed methodology integrates an improved optical flow model on a convolutional neural network to extract flow vectors with a binarization technique to assess droplets’ size and shape across the region of interest. The velocimetry approach demonstrates superior performance compared to a state-of-the-art optical flow model when applied to high-speed X-ray phase contrast spray images, achieving more accurate and reliable flow predictions. Moreover, breakup processes are quantified by breakup length and sphericity in accordance with velocity estimations, allowing a more complete characterization of the flow. This study establishes a robust methodology for analyzing spray morphology and primary breakup in compact combustors, contributing valuable means of understanding and optimizing fuel spray behavior in advanced combustion systems.

42 ENGINEERING↗

A stochastic approach to uncertainty in the equations of MHD kinematics

The magnetohydrodynamic (MHD) kinematics model describes the electromagnetic behavior of an electrically conducting fluid when its hydrodynamic properties are assumed to be known. In particular, the MHD kinematics equations can be used to simulate the magnetic field induced by a given velocity field. While prescribing the velocity field leads to a simpler model than the fully coupled MHD system, this may introduce some epistemic uncertainty into the model. If the velocity of a physical system is not known with certainty, the magnetic field obtained from the model may not be reflective of the magnetic field seen in experiments. Additionally, uncertainty in physical parameters such as the magnetic resistivity may affect the reliability of predictions obtained from this model. By modeling the velocity and the resistivity as random variables in the MHD kinematics model, we seek to quantify the effects of uncertainty in these fields on the induced magnetic field. We develop stochastic expressions for these quantities and investigate their impact within a finite element discretization of the kinematics equations. We obtain mean and variance data through Monte Carlo simulation for several test problems. Toward this end, we develop and test an efficient block preconditioner for the linear systems arising from the discretized equations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Verification of Bison fission product species conservation under TRISO reactor conditions

When assessing the reliability and predictive capabilities of a simulation tool, code verification is used to ensure that the implemented numerical algorithm is a faithful representation of its underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. During this process, numerical results in a discrete solution are compared to the analytical solution of the mathematical model. Here, in this paper, the code verification process is applied to one-dimensional spatiotemporal problems that exercise partial differential equation governing the conservation of fission product species (or mass diffusion). Numerical experiments were performed in the Bison fuel performance code to evaluate its predictive capability under various TRISO reactor conditions such as base irradiation and safety heating test conditions for either short- or long-lived fission product species, as well as a case concerning evaporation from the outer surface of a particle. The code predictions were compared with the expected exact results obtained from the analytical expressions, and the fact that they demonstrate the correct analytical behavior provides strong evidence of proper numerical algorithm implementation.

07 ISOTOPE AND RADIATION SOURCES↗

The FLUKA Code: Developments and Challenges for High Energy and Medical Applications

The FLUKA Monte Carlo code is used extensively at CERN for all beam-machine interactions, radioprotection calculations and facility design of forthcoming projects. Such needs require the code to be consistently reliable over the entire energy range (from MeV to TeV) for all projectiles (full suite of elementary particles and heavy ions). Outside CERN, among various applications worldwide, FLUKA serves as a core tool for the HIT and CNAO hadron-therapy facilities in Europe. Therefore, medical applications further impose stringent requirements in terms of reliability and predictive power, which demands constant refinement of sophisticated nuclear models and continuous code improvement. Some of the latest developments implemented in FLUKA are presented in this paper, with particular emphasis on issues and concerns pertaining to CERN and medical applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development and testing of coarse-grained models for ultrasonic simulations of cast austenitic stainless steel

Ultrasonic inspection of cast austenitic stainless steel (CASS) in the nuclear industry is particularly challenging because of sound field scatter and attenuation caused by the coarse-grained microstructure. Modeling and simulation are important tools in ultrasonic testing, as they can be used to help address key aspects of inspections, such as developing new probe designs, predicting inspection reliability, and testing phased-array focal laws. However, developing a useful and reliable CASS model is challenging due to the many grain interfaces and crystalline orientations that must be captured. We demonstrate a method of creating a realistic CASS model that is usable in CIVA, a commercially available modeling and simulation software platform. Using polished and chemically etched sections, we generate models of a coarse-grained equiaxed specimen and a columnar specimen. We also test an alternative method of generating a coarse-grained model using Voronoi regions. We qualitatively compare sound field scatter and quantitatively compare sound field attenuation and beam partitioning in simulated sound fields to those of laboratory-measured sound fields. Results show that the Voronoi models perform as well as or better than the models based on actual grain morphology. Here we also show that model-to-model randomness in Voronoi grain structure can impact the magnitude of a simulated echo response by a factor of two or more. Although CASS models are potentially a good depiction of reality for a given scenario, they should not be considered representative since CASS morphology can change significantly from specimen to specimen or within the same specimen.

36 MATERIALS SCIENCE↗

Molecular Specificity and Proton Transfer Mechanisms in Aerosol Prenucleation Clusters Relevant to New Particle Formation

Atmospheric aerosol particles influence Earth’s radiative energy balance and cloud properties either directly through interacting with the solar radiation or indirectly through acting as cloud condensation nuclei (CCN), thus impacting Earth’s climate change, air quality, and human health. Regarding both the important scientific and overarching practical implications of aerosols, the past two decades have seen an extensive research effort, with emphasis on the chemical compositions and underlying mechanisms of aerosol formation. New particle formation (NPF) has been recognized as an important pathway, contributing up to 50% of atmospheric aerosols. Nowadays, the general consensus in NPF is that it proceeds via two distinct stages—the nucleation from gaseous precursors to form critical nuclei of sub-1–2 nanometer size, and the subsequent growth into large particles. However, a fundamental understanding of both the NPF process and the molecular-level characterization of the critical size aerosol clusters is still largely missing, hampering the development of reliable and predictive aerosol nucleation and climate models.

Hou, Gao-Lei↗

Association Kinetics for Perfluorinated n -Alkyl Radicals

Radical-radical reaction channels are important in the pyrolysis and oxidation chemistry of perfluoroalkyl substances (PFAS). In particular, unimolecular dissociation reactions within unbranched n-perfluoroalkyl chains, and their corresponding reverse barrierless association reactions, are expected to be significant contributors to the gas-phase thermal decomposition of families of species such as perfluorinated carboxylic acids and perfluorinated sulfonic acids. Unfortunately, experimental data for these reactions are scarce and uncertain. Furthermore, obtaining reliable theoretical predictions for such reactions is a laborious and computationally intensive task. Here, in this work, the chemical kinetics of the various association/decomposition reactions producing/decomposing the C 2 -C 4 series of unbranched n-perfluoroalkanes (C 2 F 6 , C 3 F 8 , and C 4 F 10 ) are examined using state-of-the-art ab initio transition-state-theory-based master-equation calculations. The variable-reaction-coordinate transition-state theory (VRC-TST) formalism is employed in computing the microcanonical and canonical rates for the association reactions. Reaction thermochemistry is obtained via composite quantum chemistry calculations and the laddering of error-canceling reaction schemes via a connectivity-based hierarchy approach employing ANL1/ANL0-style reference energies. Lennard-Jones collision model parameters for the considered systems were estimated by a direct dynamics approach, and collisional energy transfer parameters were obtained from analogies to systems of similar size and heavy-atom connectivity. A one-dimensional master equation approach was used to convert the microcanonical rate coefficients from the VRC-TST analysis into temperature- and pressure-dependent rate constants for the association reactions and the reverse dissociation reactions. The data are reported in standardized formats for usage in comprehensive chemical kinetic models for PFAS thermal destruction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗