Results for “yield strength” — Page 93

DOE OSTI2020

The nature of the chemical bond and the role of non-dynamical and dynamical correlation in Be2

In the spin-coupled generalized valence bond (SCGVB) description of Be2, there is a pair of electrons in highly overlapping “inner” orbitals corresponding to a traditional σ bond, but this bond is compromised by Pauli repulsion arising from its overlap with a second “outer” pair. The presence of this outer pair of electrons leads to a repulsive potential energy curve at long range and a bound, but metastable molecule at short range. To obtain further insights into the nature of the bond in Be2, we determined the non-dynamical and dynamical correlation contributions to the potential energy curve of Be2 using four different choices for the zero-order wave function: Restricted Hartree–Fock (RHF), SCGVB, valence-CASSCF(4,4), and valence-CASSCF(4,8). The SCGVB and valence-CASSCF(4,4) wave functions yield similar breakdowns of the total correlation energy, with non-dynamical correlation being the more important contribution. For the RHF and valence-CASSCF(4,8) wave functions, dynamical correlation is critical, without which the potential energy curve is purely repulsive. High accuracy calculations on the HBen−1Be–BeBen−1H molecule as a function of n (n = 1–6) suggest that the intrinsic strength of a Be–Be σ bond uncompromised by Pauli repulsion is on the order of 62–63 kcal/mol, and its length is 2.13–2.14 Å, ∼60 kcal/mol stronger and ∼0.35 Å shorter than in Be2.

Xu, Lu. T. (ORCID:0000000182064902)↗

DOE OSTI2025

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗

NASA NTRS1993

Measurements of circulation and vorticity in the leading-edge vortex of a delta wing

The present cross-wire measurements of the flowfield above a 75-deg flat-plate delta wing have yielded distributions of velocity, axial vorticity, and circulation which exhibit strongly conical behavior upstream of the breakdown region and away from the apex and trailing edge regions. The conical character of these properties is most pronounced over the central portion of the planform, away from the apex and trailing-edge regions. This behavior is further documented by the roughly linear increase in vortex strength with distance from the apex over the forward area of the wing.

Visser, K. D.↗

NASA NTRS2003

Flightweight Carbon Nanotube Magnet Technology

Virtually all plasma-based systems for advanced airborne/spaceborne propulsion and power depend upon the future availability of flightweight magnet technology. Unfortunately, current technology for resistive and superconducting magnets yields system weights that tend to counteract the performance advantages normally associated with advanced plasma-based concepts. The ongoing nanotechnology revolution and the continuing development of carbon nanotubes (CNT), however, may ultimately relieve this limitation in the near future. Projections based on recent research indicate that CNTs may achieve current densities at least three orders of magnitude larger than known superconductors and mechanical strength two orders of magnitude larger than steel. In fact, some published work suggests that CNTs are superconductors. Such attributes imply a dramatic increase in magnet performance-to-weight ratio and offer real hope for the construction of true flightweight magnets. This Technical Publication reviews the technology status of CNTs with respect to potential magnet applications and discusses potential techniques for using CNT wires and ropes as a winding material and as an integral component of the containment structure. The technology shortfalls are identified and a research and technology strategy is described that addresses the following major issues: (1) Investigation and verification of mechanical and electrical properties, (2) development of tools for manipulation and fabrication on the nanoscale, (3) continuum/molecular dynamics analysis of nanotube behavior when exposed to practical bending and twisting loads, and (4) exploration of innovative magnet fabrication techniques that exploit the natural attributes of CNTs.

Chapman, J. N.↗

DOE OSTI2026

Artificial Intelligence for Event Reconstruction and Higgs Physics at CMS and Future Colliders

This dissertation charts a trajectory in which advances in artificial intelligence (AI) play a central role in pushing the high-energy physics frontier, complementing progress driven by higher collision energies and larger colliders. The discovery potential of the LHC and future colliders relies on accurate reconstruction of increasingly complex particle collision events. In the CMS experiment, this task is performed by the particle-flow (PF) algorithm. This dissertation presents the first implementation of a machine-learning-based particle-flow (MLPF) reconstruction in the CMS detector based on transformer architectures. In simulated top quark--antiquark pair (ttbar) events under LHC Run~3 (2023--2024) conditions, MLPF improves jet energy resolution by 10--20\% compared to standard PF for jets with transverse momentum between 30--100\GeV. Runtime performance is evaluated using simulated multijet events, with a median inference time of 20\unit{ms} per event on an NVIDIA L4 GPU, compa red to approximately 110\unit{ms} for standard PF. The MLPF algorithm is also validated on Run~3 collision data, representing the first data-validated ML-based reconstruction pipeline at any LHC experiment. We then extend MLPF toward future electron--positron colliders and introduce the first full-simulation cross-detector transfer learning workflow for PF reconstruction. The model is pre-trained on simulated events from the Compact Linear Collider detector (CLICdet) and fine-tuned on the CLIC-like detector (CLD) proposed for the Future Circular Collider (FCC). This approach achieves up to a 40\% improvement in jet energy resolution over rule-based reconstruction while reducing the required training dataset size by an order of magnitude, demonstrating the potential of AI to accelerate detector development and optimization. This dissertation also demonstrates how modern AI techniques enhance the sensitivity of LHC physics analyses. A CMS search for highly Lorentz-boosted Higgs bosons decaying to \textrm{W} boson pairs is presented, focusing on the single-lepton final state. A dedicated fine-tuning strategy for \ParT yields an approximately 70\% increase in expected sensitivity relative to the baseline model. The analysis uses proton--proton collision data at a center-of-mass energy of \ensuremath{\sqrt{s}=13\TeV} collected by CMS between 2016 and 2018, corresponding to an integrated luminosity of 138\ensuremath{\ \mathrm{fb}^{-1}}. The expected significance of the search is $1.86\sigma$, with an observed signal strength of $-0.19^{+0.48}_{-0.46}$. Finally, explainable AI techniques are applied to the MLPF and \ParticleNet algorithms using layerwise relevance propagation, showing that both models base their predictions on physically meaningful features consistent with our physics intuition. Together, these results demonstrate how advanced AI methods can enhance reconstruction, analysis sensitivity, and interpretability, shaping the next era of experimental parti cle physics.

Mokhtar, Farouk [UC, San Diego]↗

NASA NTRS1971

Electron dynamics and energy conversion in O-type linear-beam devices.

A general nonlinear interaction theory is used to investigate the effects of transverse fields (i.e., radial circuit fields and radial space-charge fields) in traveling-wave amplifiers for a variety of beam-focusing conditions. Magnetic focusing fields which are periodic or tapered (increased) with distance along the device are considered in addition to uniform magnetic fields. Results are presented for Brillouin flow and near-Brillouin flow, and the minimum magnetic field strength required to effectively constrain the electron beam is determined as a function of the operating parameters for the various focusing systems. Confined flow is also examined for the uniform-field case in order to have a basis of comparison from which the effects of radial motion of the beam electrons can be determined. The results indicate the importance of transverse effects and further yield information on the stability of strongly modulated cylindrical electron beams.-

Detweiler, H. K.↗

NASA NTRS1973

Monitoring atmospheric pollutants with a heterodyne radiometer transmitter-receiver

The presence of selected atmospheric pollutants can be determined by transmitting an infrared beam of proper wavelength through the atmosphere, and detecting the reflections of the transmitted beam with a heterodyne radiometer transmitter-receiver using part of the laser beam as a local oscillator. The particular pollutant and its absorption line strength to be measured are selected by the laser beam wave length. When the round-trip path for the light is known or measured, concentration can be determined. Since pressure (altitude) will affect the shape of the molecular absorption line of a pollutant, tuning the laser through a range of frequencies, which includes a part of the absorption line of the pollutant of interest, yields pollutant altitude data from which the altitude and altitude profile is determined.

Menzies, R. T.↗

NASA NTRS1984

Time series modeling of human operator dynamics in manual control tasks

A time-series technique is presented for identifying the dynamic characteristics of the human operator in manual control tasks from relatively short records of experimental data. Control of system excitation signals used in the identification is not required. The approach is a multi-channel identification technique for modeling multi-input/multi-output situations. The method presented includes statistical tests for validity, is designed for digital computation, and yields estimates for the frequency responses of the human operator. A comprehensive relative power analysis may also be performed for validated models. This method is applied to several sets of experimental data; the results are discussed and shown to compare favorably with previous research findings. New results are also presented for a multi-input task that has not been previously modeled to demonstrate the strengths of the method.

Biezad, D. J.↗

NASA NTRS2013

Survey of Experimental Results in High-Contrast Imaging for Future Exoplanet Missions

We present and compare experimental results in high contrast imaging representing the state of the art in coronagraph and starshade technology. These experiments have been undertaken with the goal of demonstrating the capability of detecting Earth-like planets around nearby Sun-like stars. The contrast of an Earth seen in reflected light around a Sun-like star would be about 1.2 x 10(exp -10). Several of the current candidate technologies now yield raw contrasts of 1.0 x 10(exp -9) or better, and so should enable the detection of Earths, assuming a gain in sensitivity in post-processing of a factor of 10. We present results of coronagraph and starshade experiments conducted at visible and infrared wavelengths. Cross-sections of dark fields are directly compared as a function of field angle and bandwidth. The strength and differences of the techniques are compared.

starlight suppression↗

NASA NTRS2015

Nanotubular Toughening Inclusions

Conventional toughening agents are typically rubbery materials or small molecular weight molecules, which mostly sacrifice the intrinsic properties of a matrix such as modulus, strength, and thermal stability as side effects. On the other hand, high modulus inclusions tend to reinforce elastic modulus very efficiently, but not the strength very well. For example, mechanical reinforcement with inorganic inclusions often degrades the composite toughness, encountering a frequent catastrophic brittle failure triggered by minute chips and cracks. Thus, toughening generally conflicts with mechanical reinforcement. Carbon nanotubes have been used as efficient reinforcing agents in various applications due to their combination of extraordinary mechanical, electrical, and thermal properties. Moreover, nanotubes can elongate more than 20% without yielding or breaking, and absorb significant amounts of energy during deformation, which enables them to also be an efficient toughening agent, as well as excellent reinforcing inclusion. Accordingly, an improved toughening method is provided by incorporating nanotubular inclusions into a host matrix, such as thermoset and thermoplastic polymers or ceramics without detrimental effects on the matrix's intrinsic physical properties.

Park, Cheol↗

NASA NTRS2017

Nanotubular Toughening Inclusions

Conventional toughening agents are typically rubbery materials or small molecular weight molecules, which mostly sacrifice the intrinsic properties of a matrix such as modulus, strength, and thermal stability as side effects. On the other hand, high modulus inclusions tend to reinforce elastic modulus very efficiently, but not the strength very well. For example, mechanical reinforcement with inorganic inclusions often degrades the composite toughness, encountering a frequent catastrophic brittle failure triggered by minute chips and cracks. Thus, toughening generally conflicts with mechanical reinforcement. Carbon nanotubes have been used as efficient reinforcing agents in various applications due to their combination of extraordinary mechanical, electrical, and thermal properties. Moreover, nanotubes can elongate more than 20% without yielding or breaking, and absorb significant amounts of energy during deformation, which enables them to also be an efficient toughening agent, as well as excellent reinforcing inclusion. Accordingly, an improved toughening method is provided by incorporating nanotubular inclusions into a host matrix, such as thermoset and thermoplastic polymers or ceramics without detrimental effects on the intrinsic physical properties of the matrix.

Park, Cheol↗

NASA NTRS2007

Toward the characterization of upper tropospheric clouds using Atmospheric Infrared Sounder and Microwave Limb Sounder observations

We estimate the accuracy of cloud top altitude (Z) retrievals from the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) observing suite (ZA) on board the Earth Observing System Aqua platform. We compare ZA with coincident measurements of Z derived from the micropulse lidar and millimeter wave cloud radar at the Atmospheric Radiation Measurement (ARM) program sites of Nauru and Manus islands (ZARM) and the inferred Z from vertically resolved Microwave Limb Sounder (MLS) ice water content (IWC) retrievals. The mean difference in ZA minus ZARM plus or minus one standard deviation ranges from −2.2 to 1.6 km ± 1.0 to 4.2 km for all cases of AIRS effective cloud fraction (f A) > 0.15 at Manus Island using the cloud radar only. The range of mean values results from using different approaches to determine ZARM, day/night differences, and the magnitude of f A; the variation about the mean decreases for increasing values of f A. Analysis of ZARM from the micropulse lidar at Nauru Island for cases restricted to 0.05 ≤ f A ≤ 0.15 indicates a statistically significant improvement in ZA − ZARM over the cloud radar-derived values at Manus Island. In these cases the ZA − ZARM difference is −1.1 to 2.1 km ± 3.0 to 4.5 km. These results imply that the operational ZA is quantitatively useful for constraining cirrus altitude despite the nominal 45 km horizontal resolution. Mean differences of cloud top pressure (PCLD) inferred from coincident AIRS and MLS ice water content (IWC) retrievals depend upon the method of defining AIRS PCLD (as with the ARM comparisons) over the MLS spatial scale, the peak altitude and maximum value of MLS IWC, and f A. AIRS and MLS yield similar vertical frequency distributions when comparisons are limited to f A > 0.1 and IWC > 1.0 mg m−3. Therefore the agreement depends upon the opacity of the cloud, with decreased agreement for optically tenuous clouds. Further, the mean difference and standard deviation of AIRS and MLS PCLD are highly dependent on the MLS tangent altitude. For MLS tangent altitudes greater than 146 hPa, the strength of the limb technique, the disagreement becomes statistically significant. This implies that AIRS and MLS “agree” in a statistical sense at lower tangent altitudes and “disagree” at higher tangent altitudes. These results provide important insights on upper tropospheric cloudiness as observed by nadir-viewing AIRS and limb-viewing MLS.

Wu, Dong L.↗

DOE OSTI2021

Anisotropic strength behavior of single-crystal TATB

High-rate strength behavior plays an important role in the shock initiation of high explosives, with plastic deformation serving to localize heat into hot spots and as a mechanochemical means to enhance reactivity. Recent simulations predict that detonation-like shocks produce highly reactive nanoscale shear bands in the layered crystalline explosive TATB (1,3,5-triamino-2,4,6-trinitrobenzene), but the thresholds leading to this response are poorly understood. We utilize molecular dynamics to simulate the high-rate compressive stress–strain response of TATB, with a focus on understanding flow behavior. Here, the dependence of strength on pressure and loading axis (crystal orientation) is explored. The deformation mechanisms fall broadly into two categories, with compression along crystal layers activating a buckling/twinning mode and compression normal to the layers producing nanoscale shear bands. Despite the complexity of the underlying mechanisms, the crystal exhibits relatively straightforward stress–strain curves. Most of the crystal orientations studied show rapid strain softening following the onset of yielding, which settles to a steady flow state. Trajectories are analyzed using five metrics for local states and structural order, but most of these metrics yield similar distributions for these deformation mechanisms. On the other hand, a recently proposed measure of intramolecular strain energy is found to most cleanly distinguish between these mechanisms, while also providing a plausible connection with mechanochemically accelerated decomposition kinetics. Localization of intramolecular strain energy is found to depend strongly on crystal orientation and pressure.

36 MATERIALS SCIENCE↗

NASA NTRS1987

High temperature (900-1300 C) mechanical behaviour of dendritic web grown silicon ribbons - Strain rate and temperature dependence of the yield stress

The mechanical behavior of dendritic web Si ribbons close the melting point was studied experimentally. The goal of the study was to generate data for modeling the generation of stresses and dislocation structures during growth of dendritic web Si ribbons, thereby permitting modifications to the production process, i.e., the temperature profile, to lower production costs for the photovoltaic ribbons. A laser was used to cut specimens in the direction of growth of sample ribbons, which were then subjected to tensile tests at temperatures up to 1300 C in an Ar atmosphere. The tensile strengths of the samples increased when the temperature rose above 1200 C, a phenomena which was attributed to the diffusion of oxygen atoms to the quasi-dislocation sites. The migration to the potential dislocations sites effectively locked the dislocations.

Mathews, V. K.↗

DOE OSTI2025

Approach to Evaluating Reorganization Energies of Interfacial Electrochemical Reactions

Reaction rate coefficients for electron-transfer processes at the electrode–electrolyte interface are commonly estimated by using the Butler–Volmer equation, but their values are inaccurate beyond a few tenths of volts of overpotential. The Marcus–Hush–Chidsey (MHC) formalism yields correct asymptotic behavior of the rate coefficients vs applied overpotential but has complex dependencies on the redox system’s intrinsic parameters, which can be difficult to model or measure. In this work, we bridge the two kinetics formalisms to estimate the reorganization energy, one of the important parameters for the MHC formalism, and investigate its dependence on other intrinsic parameters such as activation barriers, electronic coupling strength, and the density of states of the electrode surface. We examine the sensitivity of the reorganization energy to these parameters, establish some general relationships for accurately predicting rate coefficients using the MHC formalism over a wide range of applied overpotentials, and compare this approach to calculating MHC rate constants with other empirical approaches for the mechanisms of CO 2 reduction on different metal electrode surfaces.

Butler−Volmer↗

NASA NTRS1997

Micromechanical Modeling Efforts for Advanced Composites

Over the past two decades, NASA Lewis Research Center's in-house efforts in analytical modeling for advanced composites have yielded several computational predictive tools. These are, in general, based on simplified micromechanics equations. During the last 3 years, our efforts have been directed primarily toward developing prediction tools for high temperature ceramic matrix composite (CMC's) materials. These materials are being considered for High Speed Research program applications, specifically for combustor liners. In comparison to conventional materials, CMC's offer several advantages: high specific stiffness and strength, and higher toughness and nonbrittle failure in comparison to monolithic ceramics, as well as environmental stability and wear resistance for both roomtemperature and elevated-temperature applications. Under the sponsorship of the High Temperature Engine Materials Program (HITEMP), CMC analytical modeling has resulted in the computational tool Ceramic Matrix Composites Analyzer (CEMCAN).

Source record↗

NASA NTRS2006

NAS Demand Predictions, Transportation Systems Analysis Model (TSAM) Compared with Other Forecasts

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗

NASA NTRS2006

Utilizing Traveler Demand Modeling to Predict Future Commercial Flight Schedules in the NAS

The current work incorporates the Transportation Systems Analysis Model (TSAM) to predict the future demand for airline travel. TSAM is a multi-mode, national model that predicts the demand for all long distance travel at a county level based upon population and demographics. The model conducts a mode choice analysis to compute the demand for commercial airline travel based upon the traveler s purpose of the trip, value of time, cost and time of the trip,. The county demand for airline travel is then aggregated (or distributed) to the airport level, and the enplanement demand at commercial airports is modeled. With the growth in flight demand, and utilizing current airline flight schedules, the Fratar algorithm is used to develop future flight schedules in the NAS. The projected flights can then be flown through air transportation simulators to quantify the ability of the NAS to meet future demand. A major strength of the TSAM analysis is that scenario planning can be conducted to quantify capacity requirements at individual airports, based upon different future scenarios. Different demographic scenarios can be analyzed to model the demand sensitivity to them. Also, it is fairly well know, but not well modeled at the airport level, that the demand for travel is highly dependent on the cost of travel, or the fare yield of the airline industry. The FAA projects the fare yield (in constant year dollars) to keep decreasing into the future. The magnitude and/or direction of these projections can be suspect in light of the general lack of airline profits and the large rises in airline fuel cost. Also, changes in travel time and convenience have an influence on the demand for air travel, especially for business travel. Future planners cannot easily conduct sensitivity studies of future demand with the FAA TAF data, nor with the Boeing or Airbus projections. In TSAM many factors can be parameterized and various demand sensitivities can be predicted for future travel. These resulting demand scenarios can be incorporated into future flight schedules, therefore providing a quantifiable demand for flights in the NAS for a range of futures. In addition, new future airline business scenarios are investigated that illustrate when direct flights can replace connecting flights and larger aircraft can be substituted, only when justified by demand.

Viken, Jeff↗