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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 OSTI2024

Machine learning surrogates for surface complexation model of uranium sorption to oxides

Abstract The safety assessments of the geological storage of spent nuclear fuel require understanding the underground radionuclide mobility in case of a leakage from multi-barrier canisters. Uranium, the most common radionuclide in non-reprocessed spent nuclear fuels, is immobile in reduced form (U(IV) and highly mobile in an oxidized state (U(VI)). The latter form is considered one of the most dangerous environmental threats in the safety assessments of spent nuclear fuel repositories. The sorption of uranium to mineral surfaces surrounding the repository limits their mobility. We quantify uranium sorption using surface complexation models (SCMs). Unfortunately, numerical SCM solvers often encounter convergence problems due to the complex nature of convoluted equations and correlations between model parameters. This study explored two machine learning surrogates for the 2-pK Triple Layer Model of uranium retention by oxide surfaces if released as U(IV) in the oxidizing conditions: random forest regressor and deep neural networks. Our surrogate models, particularly DNN, accurately reproduce SCM model predictions at a fraction of the computational cost without any convergence issues. The safety assessment of spent fuel repositories, specifically the migration of leaked radioactive waste, will benefit from having ultrafast AI/ML surrogates for the computationally expensive sorption models that can be easily incorporated into larger-scale contaminant migration models. One such model is presented here.

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

Impact of soil model complexity on the long-term thermal performance prediction of a new shallow bore ground heat exchanger

Shallow bore ground heat exchangers have been investigated in recent years because they have the potential to reduce the initial cost of the ground source heat pump system. Correctly modeling the transient heat transfer between the ground heat exchanger and the surrounding soil is essential for predicting a ground heat exchanger's performance. Simplification of the soil model could increase computation speed but sacrifice accuracy. This study investigates the impact of the soil model complexity on the annual performance prediction of a new shallow bore ground heat exchanger, the underground thermal battery (UTB). A simple 1D soil model and a more detailed 2D soil model were implemented, and they were validated against a 3D soil model. Overall, the resulting predictions of the UTB’s response from the 1D and 2D models to a given thermal load in different climates were compared. The results show that the root mean square differences between the hourly temperatures of the UTB during a year predicted using the two soil models range from 1.17°C to 3.39°C. As a result, the difference in the annual power consumption of the heat pump was between 0.7% and 3.4%. Furthermore, the dimensions of the UTB affected its performance, and a longer UTB was less sensitive to the soil models.

42 ENGINEERING↗
DOE OSTI2023

Stabilization of a Heme-HNO Model Complex Using a Bulky Bis-Picket Fence Porphyrin and Reactivity Studies with NO

Nitroxyl, HNO/NO – , the one-electron reduced form of NO, is suggested to take part in distinct signaling pathways in mammals and is also a key intermediate in various heme-catalyzed NO x interconversions in the nitrogen cycle. Cytochrome P450nor (Cyt P450nor) is a heme-containing enzyme that performs NO reduction to N 2 O in fungal denitrification. The reactive intermediate in this enzyme, termed “Intermediate I”, is proposed to be an Fe-NHO/Fe-NHOH type species, but it is difficult to study its electronic structure and exact protonation state due to its instability. Here, we utilize a bulky bis-picket fence porphyrin to obtain the first stable heme-HNO model complex, [Fe(3,5-Me-BAFP)(MI)(NHO)], as a model for Intermediate I, and more generally HNO adducts of heme proteins. Due to the steric hindrance of the bis-picket fence porphyrin, [Fe(3,5-Me-BAFP)(MI)(NHO)] is stable (τ 1/2 = 56 min at -30 °C), can be isolated as a solid, and is available for thorough spectroscopic characterization. In particular, we were able to solve a conundrum in the literature and provide the first full vibrational characterization of a heme-HNO complex using IR and nuclear resonance vibrational spectroscopy (NRVS). Reactivity studies of [Fe(3,5-Me-BAFP)(MI)(NHO)] with NO gas show a 91 ± 10% yield for N 2 O formation, demonstrating that heme-HNO complexes are catalytically competent intermediates for NO reduction to N 2 O in Cyt P450nor. In conclusion, the implications of these results for the mechanism of Cyt P450nor are further discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Exploring model complexity in machine learned potentials for simulated properties

Abstract Machine learning (ML) enables the development of interatomic potentials with the accuracy of first principles methods while retaining the speed and parallel efficiency of empirical potentials. While ML potentials traditionally use atom-centered descriptors as inputs, different models such as linear regression and neural networks map descriptors to atomic energies and forces. This begs the question: what is the improvement in accuracy due to model complexity irrespective of descriptors? We curate three datasets to investigate this question in terms of ab initio energy and force errors: (1) solid and liquid silicon, (2) gallium nitride, and (3) the superionic conductor Li $$_{10}$$ 10 Ge(PS $$_{6}$$ 6 ) $$_{2}$$ 2 (LGPS). We further investigate how these errors affect simulated properties and verify if the improvement in fitting errors corresponds to measurable improvement in property prediction. By assessing different models, we observe correlations between fitting quantity (e.g. atomic force) error and simulated property error with respect to ab initio values. Graphical abstract

Rohskopf, A. (ORCID:0000000227128296)↗
DOE OSTI2023

Distance-dependent dielectric constant at the calcite/electrolyte interface: Implication for surface complexation modeling

Hypothesis: The electrical double layer formed at the mineral/electrolyte interface is often modeled using mean-field approaches based on a continuum description of the solvent whose dielectric constant is assumed to decrease monotonically with decreasing distance to the surface. In contrast, molecular simulations show that the solvent polarizability oscillates near the surface similar to the water density profile - as shown previously, for example, by Bonthuis et al. (D.J. Bonthuis, S. Gekle, R.R. Netz, Dielectric Profile of Interfacial Water and its Effect on Double-Layer Capacitance, Phys Rev Lett 107(16) (2011) 166102). Here, we showed that molecular and mesoscale pictures agree by spatially averaging the dielectric constant obtained from molecular dynamics simulations over the distances relevant to the mean-field representation. In addition, the values of capacitances used to describe the electrical double layer in Surface Complexation Models (SCMs) of the mineral/electrolyte interface can be estimated using molecularly informed spatially averaged dielectric constants and positions of hydration layers. Experiments: First, we used molecular dynamics simulations to model the calcite 101¯4/electrolyte interface. Next, by using atomistic trajectories, we calculated the distance-dependent static dielectric constant and water density in the direction normal to the. Finally, we applied spatial compartmentalization consistent with the model of parallel-plate capacitors connected in series to estimate SCM capacitances. Findings: Computationally expensive simulations are required to determine the dielectric constant profile of interfacial water near the mineral surface. On the other hand, water density profiles are readily assessable from much shorter simulation trajectories. Our simulations confirmed that dielectric and water density oscillations at the interface are correlated. Here, we parametrized linear regression models to estimate the dielectric constant directly from the local water density. This is a significant computational shortcut compared to slowly converging calculations relying on total dipole moment fluctuations. The amplitude of the interfacial dielectric constant oscillation can exceed the dielectric constant of the bulk water, suggesting an ice-like frozen state, but only if there are no electrolyte ions. The interfacial accumulation of electrolyte ions causes a decrease in the dielectric constant due to the reduction of water density and re-orientation of water dipoles in ion hydration shells. Finally, we show how to use the computed dielectric properties to estimate SCM's capacitances.

58 GEOSCIENCES↗
NASA NTRS2008

SEE Rate Estimation: Model Complexity and Data Requirements

Statistical Methods outlined in [Ladbury, TNS20071 can be generalized for Monte Carlo Rate Calculation Methods Two Monte Carlo Approaches: a) Rate based on vendor-supplied (or reverse-engineered) model SEE testing and statistical analysis performed to validate model; b) Rate calculated based on model fit to SEE data Statistical analysis very similar to case for CREME96. Information Theory allows simultaneous consideration of multiple models with different complexities: a) Model with lowest AIC usually has greatest predictive power; b) Model averaging using AIC weights may give better performance if several models have similar good performance; and c) Rates can be bounded for a given confidence level over multiple models, as well as over the parameter space of a model.

Ladbury, Ray↗
NASA NTRS2010

A Unique Computational Algorithm to Simulate Probabilistic Multi-Factor Interaction Model Complex Material Point Behavior

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points--the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Chamis, Christos C.↗
DOE OSTI2020

Utilizing Essential Symmetry Breaking in Auxiliary-Field Quantum Monte Carlo: Application to the Spin Gaps of the C 36 Fullerene and an Iron Porphyrin Model Complex

We present three distinct examples where phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) can be reliably performed with a single-determinant trial wave function with essential symmetry breaking. Essential symmetry breaking was first introduced by Lee and Head-Gordon [ Phys. Chem. Chem. Phys. 2019, 21, 4763-4778, 10.1039/C8CP07613H]. We utilized essential complex and time-reversal symmetry breaking with ph-AFQMC to compute the triplet–singlet energy gap in the TS12 set. We found statistically better performance of ph-AFQMC with complex-restricted orbitals than with spin-unrestricted orbitals. We then showed the utilization of essential spin symmetry breaking when computing the singlet–triplet gap of a known biradicaloid, C 36 . ph-AFQMC with spin-unrestricted Hartree–Fock (ph-AFQMC+UHF) fails catastrophically even with spin-projection and predicts no biradicaloid character. With approximate Brueckner orbitals obtained from regularized orbital-optimized second-order Møller–Plesset perturbation theory (κ-OOMP2), ph-AFQMC quantitatively captures strong biradicaloid character of C 36 . Lastly, we applied ph-AFQMC to the computation of the quintet–triplet gap in a model iron porphyrin complex where brute-force methods with a small active space fail to capture the triplet ground state. We show unambiguously that neither triplet nor quintet is strongly correlated using UHF, κ-OOMP2, and coupled-cluster with singles and doubles (CCSD) performed on UHF and κ-OOMP2 orbitals. There is no essential symmetry breaking in this problem. By virtue of this, we were able to perform UHF+ph-AFQMC reliably with a cc-pVTZ basis set and predicted a triplet ground state for this model geometry. The largest ph-AFQMC in this work correlated 186 electrons in 956 orbitals. Our work highlights the utility, scalability, and accuracy of ph-AFQMC with a single-determinant trial wave function with essential symmetry breaking for systems mainly dominated by dynamical correlation with little static correlation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2013

Modeling Complex Cross-Systems Software Interfaces Using SysML

The complex flight and ground systems for NASA human space exploration are designed, built, operated and managed as separate programs and projects. However, each system relies on one or more of the other systems in order to accomplish specific mission objectives, creating a complex, tightly coupled architecture. Thus, there is a fundamental need to understand how each system interacts with the other. To determine if a model-based system engineering approach could be utilized to assist with understanding the complex system interactions, the NASA Engineering and Safety Center (NESC) sponsored a task to develop an approach for performing cross-system behavior modeling. This paper presents the results of applying Model Based Systems Engineering (MBSE) principles using the System Modeling Language (SysML) to define cross-system behaviors and how they map to crosssystem software interfaces documented in system-level Interface Control Documents (ICDs).

Earth orbit↗
NASA NTRS2011

Handling Qualities Evaluations of Low Complexity Model Reference Adaptive Controllers for Reduced Pitch and Roll Damping Scenarios

National Aeronautics and Space Administration (NASA) researchers have conducted a series of flight experiments designed to study the effects of varying levels of adaptive controller complexity on the performance and handling qualities of an aircraft under various simulated failure or damage conditions. A baseline, nonlinear dynamic inversion controller was augmented with three variations of a model reference adaptive control design. The simplest design consisted of a single adaptive parameter in each of the pitch and roll axes computed using a basic gradient-based update law. A second design was built upon the first by increasing the complexity of the update law. The third and most complex design added an additional adaptive parameter to each axis. Flight tests were conducted using NASA s Full-scale Advanced Systems Testbed, a highly modified F-18 aircraft that contains a research flight control system capable of housing advanced flight controls experiments. Each controller was evaluated against a suite of simulated failures and damage ranging from destabilization of the pitch and roll axes to significant coupling between the axes. Two pilots evaluated the three adaptive controllers as well as the non-adaptive baseline controller in a variety of dynamic maneuvers and precision flying tasks designed to uncover potential deficiencies in the handling qualities of the aircraft, and adverse interactions between the pilot and the adaptive controllers. The work was completed as part of the Integrated Resilient Aircraft Control Project under NASA s Aviation Safety Program.

Hanson, Curt↗
DOE OSTI2024

Time-Resolved X-ray Emission Spectroscopy and Synthetic High-Spin Model Complexes Resolve Ambiguities in Excited-State Assignments of Transition-Metal Chromophores: A Case Study of Fe-Amido Complexes

To fully harness the potential of abundant metal coordination complex photosensitizers, a detailed understanding of the molecular properties that dictate and control the electronic excited-state population dynamics initiated by light absorption is critical. In the absence of detectable luminescence, optical transient absorption (TA) spectroscopy is the most widely employed method for interpreting electron redistribution in such excited states, particularly for those with a charge-transfer character. The assignment of excited-state TA spectral features often relies on spectroelectrochemical measurements, where the transient absorption spectrum generated by a metal-to-ligand charge-transfer (MLCT) electronic excited state, for instance, can be approximated using steady-state spectra generated by electrochemical ligand reduction and metal oxidation and accounting for the loss of absorptions by the electronic ground state. However, the reliability of this approach can be clouded when multiple electronic configurations have similar optical signatures. Using a case study of Fe(II) complexes supported by benzannulated diarylamido ligands, we highlight an example of such an ambiguity and show how time-resolved X-ray emission spectroscopy (XES) measurements can reliably assign excited states from the perspective of the metal, particularly in conjunction with accurate synthetic models of ligand-field electronic excited states, leading to a reinterpretation of the long-lived excited state as a ligand-field metal-centered quintet state. Furthermore, a detailed analysis of the XES data on the long-lived excited state is presented, along with a discussion of the ultrafast dynamics following the photoexcitation of low-spin Fe(II)-N amido complexes using a high-spin ground-state analogue as a spectral model for the 5 T 2 excited state.

14 SOLAR ENERGY↗
DOE OSTI2021

Quantitative Account of the Bonding Properties of a Rubredoxin Model Complex [Fe(SCH3)4]q, q = -2, -1, +2, +3

Iron-sulfur clusters play important roles in biology as parts of electron transfer chains and catalytic cofactors. Here, we report a detailed computational analysis of a structural model of the simplest natural iron-sulfur cluster of rubredoxin and its cationic counterparts. Specifically, we report results for the ground and low-lying electronically excited states of the complex [Fe(SCH3)4]2-/1-/2+/3+, using Multi-Reference (CASSCF, MRCISD), and Coupled Cluster [CCSD(T)] methodology in order to provide accurate adiabatic reduction energies, dissociation energies and insights into the bonding analysis. The nature of the Fe-S chemical bond and the magnitude of the ionization potentials in the anionic and cationic [Fe(SCH3)4] complexes offer a physical rationale for the relative stabilization, structure and speciation of these complexes. Anionic and cationic complexes present different types of chemical bonds: prevalently ionic in [Fe(SCH3)4]2-/1- complexes and covalent in [Fe(SCH3)4]2+/3+ complexes. The ionic bonds result in an energy gain for the transition [Fe(SCH3)4]2-®[Fe(SCH3)4]- (i.e., FeII®FeIII) of 1.5 eV, while the covalent bonds result in an energy loss for the transition [Fe(SCH3)4]2+®[Fe(SCH3)4]3+ of 16.6 eV, almost half of the IP of Fe2+. The ionic vs covalent bond character influences the Fe-S bond strength and length, i.e., ionic Fe-S bonds are longer than covalent ones by about 0.2 Å (for FeII) and 0.04 Å (for FeII). Finally, the average Fe-S heterolytic bond strength is 6.7 eV (FeII) and 14.6 (FeIII) eV at the RCCSD(T) level of theory.

Tzeli, Demeter↗
NASA NTRS1993

Aerodynamic optimization of an HSCT configuration using variable-complexity modeling

An approach to aerodynamic configuration optimization is presented for the high-speed civil transport (HSCT). A method to parameterize the wing shape, fuselage shape and nacelle placement is described. Variable-complexity design strategies are used to combine conceptual and preliminary-level design approaches, both to preserve interdisciplinary design influences and to reduce computational expense. Conceptual-design-level (approximate) methods are used to estimate aircraft weight, supersonic wave drag and drag due to lift, and landing angle of attack. The drag due to lift, wave drag and landing angle of attack are also evaluated using more detailed, preliminary-design-level techniques. New, approximate methods for estimating supersonic wave drag and drag due to lift are described. The methodology is applied to the minimization of the gross weight of an HSCT that flies at Mach 2.4 with a range of 5500 n.mi. Results are presented for wing planform shape optimization and for combined wing and fuselage optimization with nacelle placement. Case studies include both all-metal wings and advanced composite wings.

Hutchison, M. G.↗