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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Convergent Concordant Mode Approach for Molecular Vibrations: CMA-2

The concordant mode approach (CMA) is a promising new scheme for dramatically increasing the system size and level of theory achievable in quantum chemical computations of molecular vibrational frequencies. Here, we achieve advances in the CMA hierarchy by computations targeting CCSD(T)/cc-pVTZ (coupled cluster singles and doubles with perturbative triples using a correlation-consistent polarized-valence triple-ζ basis set) benchmarks within the G2 molecular test set, executing a statistical analysis for 1501 frequencies from 111 compounds and then separately solving the refractory case of pyridine. First, MP2/cc-pVTZ (second-order Møller–Plesset perturbation theory with the same basis set) proves to be an excellent and preferred choice for generating the underlying (Level B) normal modes of the CMA scheme. Utilizing this Level B within the CMA-0A method reproduces the 1501 benchmark frequencies with a mean absolute error (MAE) of only 0.11 cm –1 and an attendant standard deviation of 0.49 cm –1 . Second, a convergent CMA-2 method is constituted that allows efficient computation of higher level (Level A) frequencies to any reasonable accuracy threshold by using only Hartree–Fock (HF) and MP2 or density functional theory (DFT) data to generate ξ parameters, which select the sparse off-diagonal force field elements for explicit evaluation at Level A. When Level B = MP2/cc-pVTZ, a cutoff of ξ = 0.02 provides an average maximum absolute error per molecule of only 0.17 cm –1 by incurring merely a 33% increase in average cost over CMA-0A. This CMA-2 method also eradicates the 4 problematic CMA-0A outliers of pyridine with even less effort (ξ = 0.04, 22% increase). Finally, the newly developed CMA procedures are shown to be highly successful when applied to 1-(1H-pyrrol-3-yl)ethanol, a new test molecule with diverse types of vibration.

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

Minimum feature size control in level set topology optimization via density fields

A level set topology optimization approach that uses an auxiliary density field to nucleate holes during the optimization process and achieves minimum feature size control in optimized designs is explored. The level set field determines the solid-void interface and the density field describes the distribution of a fictitious porous material using the solid isotropic material with penalization. These fields are governed by two sets of independent optimization variables which are initially coupled using a penalty for hole nucleation. The strength of the density field penalization and projection is gradually increased during the optimization process to promote a 0-1 density distribution. In addition, a second penalty regulates the evolution of the density field in the void phase. The treatment of the density field combined with the second penalty mitigate the appearance of small design features. The minimum feature size of optimized designs is controlled by the radius of the linear filter applied to the density optimization variables. The structural response is predicted by the extended finite element method, the sensitivities by the adjoint method, and the optimization variables are updated by a gradient-based optimization algorithm. Numerical examples investigate the robustness of this approach with respect to algorithmic parameters and mesh refinement. The results show the applicability of the combined density level set topology optimization approach for both optimal hole nucleation and for minimum feature size control in 2D and 3D. This comes, however, at the cost of a more complex problem formulation and additional computational cost due to an increased number of optimization variables.

42 ENGINEERING↗
DOE OSTI2022

SMALE: Enhancing Scalability of Machine Learning Algorithms on Extreme-Scale Computing Platforms

Deployment and execution of machine learning tasks on extreme-scale computing platforms face several significant technical challenges: 1) High computing cost incurred by dense networks – The computing workload of deep networks with densely-connected topology increases rapidly with the network size, imposing a non-scalable computing model of extreme-scale computing platforms; 2) Non-optimized workload distribution – Many advanced deep learning algorithms, e.g., sparsification and irregular net-work topology, produce very unbalanced workload distribution on extreme-scale computing platforms. The computation efficiency is greatly hindered by the incurred data and computation redundancies as well as long tails of the node with extensive workload; 3) Constraints in data movement and I/O bottle-neck – Inter-node data movement in extreme-scale computing platforms are associated with high energy and latency costs, and subject to the constraints of I/O bandwidth; and 4) Generalization of algorithm realization and acceleration on computing platforms – The large varieties of machine learning algorithms and structures of extreme-scale computing platforms make the derivation of a generalized algorithm realization and acceleration method very challenging, which, however, is the requirement by domain scientists and interested users. We call the above challenges Smale’s Problems in Machine Learning and Understanding for High-Performance Computing Scientific Discovery. The objective of our three-year research project is to develop a holistic innovation set at structure, assembly, and acceleration layers of machine learning algorithms to address the above challenges in algorithm deployment and execution. Three tasks are particularly performed, including: At the algorithm structure level, we investigate the techniques that can structurally sparsify on the topology of deep networks for computing workload reduction. We also study clustering and pruning techniques that can optimize the workload distributions over the extreme-scale computing platforms; At the algorithm assembly level, we derive a unified learning framework for unsupervised transfer learning and dynamic growing capabilities. Novel training methods are also exploited to enhance the training efficiency of the proposed framework; At the algorithm acceleration level, we will develop a series of techniques that can accelerate the computation of sparse matrix operations, which are one of the core executions in deep learning and optimize memory access of the concerned platforms. Our proposed techniques attack the fundamental problems in machine learning algorithms running on extreme-scale computing platforms by vertically integrating the solutions at three closely entangled layers, paving the long-term scaling path of machine learning applications under DOE context. Three tasks corresponding to the above respective research orientations are performed during the three-year project period with our collaborators at ORNL. The outcome of the proposed project is anticipated to form a holistic solution set of novel algorithms and network topologies, efficient training techniques, and fast acceleration methods to promote the computing scalability of the machine learning applications of particular interest to DOE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Assessment of wind power scenario creation methods for stochastic power systems operations

Probabilistic scenarios of renewable energy production, such as wind, have been gaining popularity for use in stochastic variants of power systems operations scheduling problems, allowing for optimal decision-making under uncertainty. The quality of the scenarios has a direct impact on the value of the resulting decisions, but until now, methods for creating scenarios have not been compared under realistic operational conditions. Here, we compare the quality of scenario sets created using three different methods, based on a simulated re-enactment of stochastic day-ahead unit commitment and subsequent dispatch for a realistic test system. We create scenarios using a dataset of forecasted and actual wind power values, scaled to evaluate the effects of increasing wind penetration levels. We show that the choice of scenario set can significantly impact system operating cost, renewable energy use, and the ability of the system to meet demand. This result has implications for the ability of system operators to efficiently integrate renewable production into their day-ahead planning, highlighting the need for the use of performance-based assessments for scenario evaluation.

17 WIND ENERGY↗
NASA NTRS1985

Advanced reliability methods for structural evaluation

Fast probability integration (FPI) methods, which can yield approximate solutions to such general structural reliability problems as the computation of the probabilities of complicated functions of random variables, are known to require one-tenth the computer time of Monte Carlo methods for a probability level of 0.001; lower probabilities yield even more dramatic differences. A strategy is presented in which a computer routine is run k times with selected perturbed values of the variables to obtain k solutions for a response variable Y. An approximating polynomial is fit to the k 'data' sets, and FPI methods are employed for this explicit form.

Wirsching, P. H.↗
NASA NTRS1994

The Fraternal Twins of Quartet O4(+)

Eleven stationary geometries of quartet O4(+) have been studied by ab initio methods. The geometries were optimized at the Complete Active Space Self-Consistent Field (CASSCF) level of theory and the energies were calculated by the multiconfigurational second order pertubation method (CASPT2), using Double-Zeta Plus polarization (DZP), Triple-Zeta Plus Double Polarization (TZ2P), average Atomic Natural Orbital (ANO) (5s4p2d) and average ANO (6s5p3d2f) basis sets. The rectangular and trans-planar structures are found to be the most stable, with an energy barrier to conversion between the two at the threshold of dissociation. Both have a delocalized hole and are stable relative to separated 02 and 02(+)by 11.0 and 11.5 kcal/mol for the rectangular and the 2 trans-planar structure, respectively, compared with the experimentally deduced energy in the range of 9.2 to 10.8 kcal/mol. The adiabatic ionization potentials of 04 and 02 are computed to be 11.67 and 12.21 eV, while experimental values are 11.66 and 12.07 eV, respectively. The vibrational frequencies have been computed for all degrees of freedom at the CASSCF level of theory. Symmetry breaking is found to be a particular problem in the computation of the antisymmetric stretch frequency for the delocalized structures at the CASSCF level of theory. Attempts to rectify these problems using the restricted active space self-consistent field (RASSCF) method leads to additional difficulties, but further analysis yields insight into the symmetry breaking and problems with earlier calculations. Finally, a nonorthogonal configuration interaction (CI) calculation based on the interaction of localized CASSCF wave functions using the Complete Active Space State Interation (CASSI) method leads to a balanced treatment of the antisymmetric stretch which is free from symmetry breaking. The study explains the four most prominent absorption frequencies observed in the partially unassigned IR spectrum of O4(+) isolated in solid neon as the antisymmetric OO stretch, and the combination band of the symmetric and antisymmetric 00 stretch of both the rectangular and trans-planar structures.

Lindh, Roland↗
DOE OSTI2021

Effects of finite element discretization and model simplification on calculations of ductile failure initiation

The finite element method is a scheme to discretize the infinite number of degrees of freedom in continuum-level problems down to a finite number of degrees of freedom. This discretization is done in conjunction with methods that also reduce the field differential equations to sets of algebraic ones that can be solved by arithmetical operations. Therefore, solutions attained by finite element models are approximations to the exact solutions of the field equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Success Path Method: Implementation Guidance

This document provides a guide regarding the application of the Argonne National Laboratory (Argonne) Success Path Method (SPM) for the management of risk(s) of processes associated with organizational objectives. The current work provides an approach to implement the set of standard (higher level) requirements for the SPM. A companion document for Process Specific Applications, which is current under development, provides additional guidance regarding how the general implementation description detailed here can be adapted to the evaluation of specific processes.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Bond length, dipole moment, and harmonic frequency of CO

A detailed comparison of some properties of CO is given, at the modified coupled-pair functional, single and double excitation coupled-cluster (CCSD), and CCSD(T) levels of theory (including a perturbational estimate for connected triple excitations), using a variety of basis sets. With very large one-particle basis sets, the CCSD(T) method gives excellent results for the bond distance, dipole moment, and harmonic frequency of CO. In a (6s 5p 4d 3f 2g 1h) + (1s 1p 1d) basis set, the bond distance is about 0.005a0 too large, the dipole moment about 0.005 a.u. too small, and the frequency about 6/cm too small, when compared with experimental results.

Barnes, Leslie A.↗
NASA NTRS1992

Theoretical study of the bonding of the first- and second-row transition-metal positive ions to methylene

The geometries of the molecules formed by the interaction of the first- and second-row transition-metal cations with methylene are optimized at the modified coupled-pair functional (MCPF) level of theory using large Gaussian basis sets, and their dissociation energies are computed employing both the MCPF and internally contracted averaged coupled-pair functional (ICACPF) methods. The computed binding energies are generally in good agreement with the available experimental results, although the calculations indicate that the experimental values for ScCH2(+), TiCH2(+), and NbCH2(+) are probably too large. The nature of the bonding in each case and trends in the bonding patterns across the transition-metal rows are discussed.

Bauschlicher, Charles W., Jr.↗
NASA NTRS2011

Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits or Instrument Simulators

The properties of clouds that may be observed by satellite instruments, such as optical depth and cloud top pressure, are only loosely related to the way clouds m-e represented in models of the atmosphere. One way to bridge this gap is through "instrument simulators," diagnostic tools that map the model representation to synthetic observations so that differences between simulator output and observations can be interpreted unambiguously as model error. But simulators may themselves be restricted by limited information available from the host model or by internal assumptions. This paper considers the extent to which instrument simulators are able to capture essential differences between MODIS and ISCCP, two similar but independent estimates of cloud properties. The authors review the measurements and algorithms underlying these two cloud climatologies, introduce a MODIS simulator, and detail data sets developed for comparison with global models using ISCCP and MODIS simulators, In nature MODIS observes less mid-level doudines!> than ISCCP, consistent with the different methods used to determine cloud top pressure; aspects of this difference are reproduced by the simulators running in a climate modeL But stark differences between MODIS and ISCCP observations of total cloudiness and the distribution of cloud optical thickness can be traced to different approaches to marginal pixels, which MODIS excludes and ISCCP treats as homogeneous. These pixels, which likely contain broken clouds, cover about 15 k of the planet and contain almost all of the optically thinnest clouds observed by either instrument. Instrument simulators can not reproduce these differences because the host model does not consider unresolved spatial scales and so can not produce broken pixels. Nonetheless, MODIS and ISCCP observation are consistent for all but the optically-thinnest clouds, and models can be robustly evaluated using instrument simulators by excluding ambiguous observations.

Ackerman, Steven A.↗
NASA NTRSDate not supplied

Spacecraft Cabin Ventilation Fan Research at NASA

NASA has recently made the geometry and solid model for a spacecraft cabin ventilation fan prototype available to the public via electronic file downloads from the NASA Technical Report Server. This fan can be used for research and development by many organizations. The fan is 3.5 inches in diameter, 9 inches long, and weighed 3.6 lb. The NASA Quiet Space Fan was designed to make 3.64 inches of water pressure rise at 150.3 cfm of airflow at 12,000 rpm at standard air conditions of 70ºF and 14.7 psia. The performance of the metal version of the fan was measured to be 3.48 inches of water at 150.6 cfm at design speed. A low-noise blade-vane count was chosen to try to reduce tone noise generated by this fan by cutting off the first three blade passing frequency tones. In-duct microphone array measurements indicated that the most evident tones occur for frequencies of 1800 Hz (1 BPF) and 7200 Hz (4 BPF). Using reverberant room standard testing methods, the A-weighted sound power level for the fan operating at design point conditions was measured to be 71 dBA. This report describes the current set of publicly available information for this fan. The fan was designed, optimized, and tested with tools and techniques that NASA has traditionally used for turbofan engine research. This is one way that technology developed for aerospace applications can be used more broadly, since quiet and efficient fans are needed for many ventilation systems on spacecraft, aircraft, watercraft, land vehicles, and buildings.

fan, noise, ventilation↗
NASA NTRSDate not supplied

Spacecraft Cabin Ventilation Fan Research at NASA

NASA has recently made the geometry and solid model for a spacecraft cabin ventilation fan prototype available to the public via electronic file downloads from the NASA Technical Reports Server. This fan can be used for research and development by many organizations. The NASA Quiet Space Fan is 8.89 cm (3.50 in) in diameter, 22.9 cm (9.00 in) long, and the metal fan weighs 1.63 kg (3.6 lbm). The fan was designed to generate a system total pressure rise of 906 Pa (3.64 inches of water) at 0.709 m3/s (150.3 cfm) of airflow at 12,000 rpm (at 21.1ºC (70ºF) and 14.7 psia). Performance measured using standardized techniques showed good agreement with design and predicted values. A low-noise blade-vane count was chosen to reduce tonal noise generated by rotor-stator interaction for the first three blade passing frequency harmonics. In-duct microphone array measurements indicated that the most evident tones occur at frequencies of 1,800 Hz (1 BPF) and 7,200 Hz (4 BPF). Using reverberant room standard testing methods, the A-weighted sound power level for the fan operating at design point conditions was measured to be 71 dBA. This report describes the current set of publicly available information for this fan. The fan was designed, optimized, and tested with tools and techniques that NASA has traditionally used for turbofan engine research. This demonstrates that technology developed for aerospace applications can be used more broadly, since quiet and efficient fans are needed for many ventilation systems in spacecraft, aircraft, watercraft, land vehicles, and buildings.

fan↗
NASA NTRSDate not supplied

Inferred Sea Level Prediction in the NASA GMAO Seasonal Forecasting System

Reliable predictions of sea level anomalies on seasonal timescales with lead times of 1 to 9 months may have relevance to stakeholders – for example, in the advance deployment of resources for coastal flood mitigation. Routine prediction and analysis may also highlight physical processes associated with sea level change and modeling capabilities on seasonal and other timescales. These forecasts may represent interannual changes in the seasonal slope of the ocean surface, teleconnection effects such as the El Niño/Southern Oscillation phenomenon, and variations in seasonal hydrology including precipitation and coastal runoff. Coupled atmosphere/ocean models are routinely used in the seasonal prediction of temperature anomalies, precipitation anomalies, sea ice cover, and climate indices such as the Niño3.4 predictions under the North American Multi-Model Ensemble (NMME) protocol. Within the limits of their configuration, these complex Earth-system models have a potential for depicting regional changes in oceanic column properties, including the sea surface height. Seasonal prediction models generally have no representation of long-term mass contributions from melting land ice, or changes in vertical land motion; their output may be more specifically characterized as predictions of the ocean dynamic sea level. In practice however, the sea surface height prognostic variable is substantially compromised by the forecast model response to initial conditions. Imbalances between the initial, observed hydrologic cycle and the forecast model state produce abrupt adjustments in the model sea surface height. As a result, most seasonal prediction systems employ a constraint on the globally-averaged sea surface height that is applied at each time step. This essentially renders the prognostic sea surface height variable as unserviceable. Several approaches have previously been used to retrieve sea level information from seasonal forecasts beyond the use of the sea surface height variable. Here, we extend a method of relating other prognostic values, including ocean circulation and climate indices, to observed sea level variations. We use the merged altimetry record of the NASA MEaSUREs Gridded Sea Surface Height Anomalies data set and monthly revised local reference gauge observations from the National Oceanography Centre Permanent Service for Mean Sea Level (PSMSL) to evaluate derived prognostic variables from the NASA Global Modeling and Assimilation Office subseasonal-to-seasonal system version 2.1 (GMAO S2S v2.1). We focus on results for the midlatitudes with particular emphasis on US gauge locations. As shown in previous studies, prognostic ENSO-related indices in boreal winter are well correlated with gauge observations for the US west coast, but also for other locations in the southeastern US. Other forecast climate indices such as the North Atlantic Oscillation have relations to sea level that are limited both seasonally and spatially. As expected, surface atmospheric pressure (e.g., inverse barometer effect) is found to be particularly well correlated with observed sea level. We provide a characterization of forecast skill for seasonal sea level with this method.

Richard I Cullather↗
NASA NTRS1991

A method for selecting an operations concept to achieve successful mission operations

A procedure is presented for mapping operations concepts into design alternatives for a data system to be used in a generic ground based control center. A set of descriptive categories are developed to characterize the operational environment that relate to responsiveness, automation, and commitment. The operations concept is then developed according to a hierarchical decomposition of a mission statement into lower-level tasks, and the interpretation of the model's output is addressed. The method permits the description of operations concepts in terms of concept categories and ranges of alternatives between those categories. The descriptive framework can provide a mechanism for analyzing competing operations concepts.

Hornstein, Rhoda S.↗
NASA NTRS2000

Predictability of Gaseous Impact Ignition Sensitivity from Autoignition Temperature Data

An analysis of cumulative binomial probabilities for a quantal-type test like ASTM G74 indicates that for a probability of reaction in a single trial of 0.05, the probability of obtaining zero reactions in 20 trials is only approximately 36 percent, Because the lack of precision with the ASTM G74 test logic could be potentially misleading, an investigation was conducted to determine if pneumatic impact sensitivity could be predicted more reliably from other, more precise test methods. Pneumatic impact sensitivity tests were conducted following ASTM G74, but employing more rigorous test logics; autoignition temperature tests were conducted per ASTM G72. Polytetrafluoroethylene (PTFE), Viton A, polyethylene, polyoxymethylene polyamide, and silicone were the polymers used. After a fixed number of pneumatic impact tests was performed at set pressures, a plot of reaction frequency over a 3.4 to 24.1 MPa impact pressure range indicated that PTFE, Viton A, and silicone would outperform other polymers. The 50 percent pneumatic impact reactivity level was determined with the Bruceton test method. The data obtained resulted in a strong correlation between the 50 percent reactivity level and the autoignition temperature of polymers, indicating similar ignition mechanisms.

Hirsh, David↗
DOE OSTI2021

Elaborated thermochemical treatment of HF, CO, N 2 , and H 2 O: Insight into HEAT and its extensions

Here, empirical, highly accurate non-relativistic electronic total atomization energies (eTAEs) are established by combining experimental or computationally converged treatments of the nuclear motion and relativistic contributions with the total atomization energies of HF, CO, N 2 , and H 2 O obtained from the Active Thermochemical Tables. These eTAEs, which have estimated (2σ) uncertainties of less than 10 cm -1 (0.12 kJ mol -1 ), form the basis for an analysis of high-level ab initio quantum chemical calculations that aim at reproducing these eTAEs for the title molecules. The results are then employed to analyze the performance of the high-accuracy extrapolated ab initio thermochemistry, or High-Accuracy Extrapolated Ab Initio Thermochemistry (HEAT), family of theoretical methods. The method known as HEAT-345(Q), in particular, is found to benefit from fortuitous error cancellation between its treatment of the zero-point energy, extrapolation errors in the Hartree-Fock and coupled cluster contributions, neglect of post-(T) core-correlation, and the basis-set error involved in higher-level correlation corrections. In addition to shedding light on a longstanding curiosity of the HEAT protocol—where the cheapest HEAT-345(Q) performs comparably to the theoretically more complete HEAT-456QP procedure—this study lays the foundation for extended HEAT variants that offer substantial improvements in accuracy relative to the established approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Application of multigrid and adaptive grid embedding to the two-dimensional flux-split Euler equations

A numerical algorithm is presented for solving the two-dimensional flux-split Euler equations using a multigrid method with adaptive grid embedding. The method uses an unstructured data set along with a system of pointers for communication on the irregularly shaped grid topologies. An explicit two-stage time-advancement scheme is implemented. A multigrid algorithm is used to provide grid level communication and to accelerate the convergence of the solution to steady state. Results are presented for a NACA 0012 aerofoil in a free stream with a Mach number of 0.85 and an angle of attack of 1.0 degree. Excellent resolution of the shock structures is obtained with the adaptive grid embedding method with significantly fewer grid points than the comparable structured grid.

Warren, Gary P.↗