Use of grit-type boundary-layer transition trips on wind-tunnel models
Guidelines applicable to grit-type boundary layer transition trips near leading edges of wind tunnel models
BOUNDARY LAYER TRANSITION↗
SEARCH · Engineering Papers
Results for “model types”
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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Assessing Cognitive Impacts of Errors from Machine Learning and Deep Learning Models: Final Report
Due to their recent increases in performance, machine learning and deep learning models are being increasingly adopted across many domains for visual processing tasks. One such domain is international nuclear safeguards, which seeks to verify the peaceful use of commercial nuclear energy across the globe. Despite recent impressive performance results from machine learning and deep learning algorithms, there is always at least some small level of error. Given the significant consequences of international nuclear safeguards conclusions, we sought to characterize how incorrect responses from a machine or deep learning-assisted visual search task would cognitively impact users. We found that not only do some types of model errors have larger negative impacts on human performance than other errors, the scale of those impacts change depending on the accuracy of the model with which they are presented and they persist in scenarios of evenly distributed errors and single-error presentations. Further, we found that experiments conducted using a common visual search dataset from the psychology community has similar implications to a safeguards- relevant dataset of images containing hyperboloid cooling towers when the cooling tower images are presented to expert participants. While novice performance was considerably different (and worse) on the cooling tower task, we saw increased novice reliance on the most challenging cooling tower images compared to experts. These findings are relevant not just to the cognitive science community, but also for developers of machine and deep learning that will be implemented in multiple domains. For safeguards, this research provides key insights into how machine and deep learning projects should be implemented considering their special requirements that information not be missed.
97 MATHEMATICS AND COMPUTING↗
Application of artificial intelligence methods in the international roughness index prediction of rigid and composite pavements: a systematic review
The International Roughness Index (IRI) is a widely adopted metric for quantifying pavement roughness, directly influencing vehicle safety, ride comfort, and overall roadway performance. In recent years, the use of Machine Learning (ML) models for IRI prediction has gained momentum, with the goal of improving the allocation of maintenance and rehabilitation resources by enabling accurate assessments of pavement conditions. Most prior reviews, however, have concentrated on flexible pavements, leaving a notable gap regarding rigid and composite pavements. To address this gap, the present study conducts a systematic review of Artificial Intelligence (AI) methods applied to IRI prediction for rigid and composite pavements. Literature published between 2004 and 2025 is synthesized to highlight prevailing trends, methodological contributions, and directions for future research. Particular attention is given to the types of models employed, the datasets used for training and validation, and the role of input variables and data-processing strategies. Across the included studies, ensemble learning methods (especially gradient boosting variants such as XGBoost), artificial neural networks, and hybrid architectures frequently achieved high predictive skill, with several models reporting test-set coefficients of determination approaching 0.9–0.96, indicating strong potential for capturing the influence of traffic, pavement structure, and climatic factors. Since these results are obtained from heterogeneous datasets and evaluation protocols, they are interpreted qualitatively rather than as strict cross-study rankings. Analysis of input variables revealed that pavement age and initial IRI were included in 91% (21 of 23) and 78% (18 of 23) of studies, respectively. Climatic variables such as the freezing index appeared in 57% (13 of 23), while traffic-related factors were considered in 65% (15 of 23). The findings underscore the importance of standardized, high-quality datasets, such as those from the Long-Term Pavement Performance (LTPP) program, along with data consistency, model interpretability, computational efficiency, and replicability in enhancing IRI prediction. Future research should focus on incorporating input variable selection techniques to identify the most influential predictors, thereby improving accuracy and robustness. Integrating these approaches with advanced non-linear data-driven models, coupled with robust hyperparameter optimization, holds considerable promise for strengthening the reliability of IRI prediction and supporting resilient pavement management strategies.
42 ENGINEERING↗
Mid-infrared rotational line emission from interstellar molecular hydrogen
The line emission from the v = 0-0 S(0), S(2), and S(3), and the v = 1-0 and v = 2-1 S(1) transitions of molecular hydrogen in clouds exposed to high FUV fluxes and in shocks is modeled. Particular attention is given to the lowest pure rotational H2 transitions at 20 and 17 microns, respectively. It is found that, in photodissociation regions (PDRs), the emission comes from warm (greater than about 100 k) molecular gas, situated at optical depths greater than about 1, beyond the hot atomic surface layer of the clouds. For FUV fields, G0 = 1000 to 100,000 times the average interstellar field densities n = 10 exp 3 - 10 exp 7/cu cm, the typical line intensities are in the range 10 exp -6 to 10 exp -4 ergs/s sq cm sr. The predictions for the line intensities from both C-type and J-type shock models are compared. The results are applied to recent observations of the 0-0 S(1) transition in both the PDR and the shocked gas in Orion.
Burton, Michael G.↗
Probing bottom-associated production of a TeV scale scalar decaying to a top quark and dark matter at the LHC
Abstract A minimal non-thermal dark matter model that can explain both the existence of dark matter and the baryon asymmetry in the universe is studied. It requires two color-triplet, iso-singlet scalars with$$ \mathcal{O}\left(\textrm{TeV}\right) $$ O TeV masses and a singlet Majorana fermion with a mass of$$ \mathcal{O}\left(\textrm{GeV}\right) $$ O GeV . The fermion becomes stable and can play the role of the dark matter candidate. We consider the fermion to interact with a top quark via the exchange of QCD-charged scalar fields coupled dominantly to third generation fermions. The signature of a single top quark production associated with a bottom quark and large missing transverse momentum opens up the possibility to search for this type of model at the LHC in a way complementary to existing monotop searches.
Physics↗
Comparison on the properties of ITZs in fly ash-based geopolymer and Portland cement concretes with equivalent flowability
Highlights: • Modelled ITZs can effectively avoid the effects caused by different factors and test locations of ITZ. • ITZ properties of PC and geopolymer concretes are compared based on equivalent flowability of binders. • Geopolymer ITZ exhibits stronger bonding than that of PC, and higher mechanical properties than geopolymer paste. • Strong ITZs in geopolymer concrete are attributed to the layer of gel-rich paste with dense microstructures. • Elastic modulus and hardness properties of ITZs in PC concrete are increased due to the CH crystals. This paper aims to compare the properties of interfacial transition zones (ITZs) in Portland cement (PC) concrete and geopolymer concrete. Portland cement and geopolymer pastes were designed with the equivalent flowability to provide similar mix and casting condition of ITZs. Two types of modelled ITZs were prepared to facilitate the nanoindentations across ITZs, microstructural characterization, and comparison on the properties of ITZs with less influential factors. The results showed that the interfacial bonding of ITZs between geopolymer matrix and aggregate is relatively stronger than the counterpart in the PC concrete. There is a high amount of crystalline hydration products in the ITZs of PC concrete, but a layer gel-rich paste with denser microstructures in the ITZs of geopolymer concrete. Additionally, the interface morphology and nanoindentation analysis indicate that the property of ITZs in the modelled geopolymer concrete is not poorer than that of the corresponding geopolymer paste.
36 MATERIALS SCIENCE↗
Out of Plane Stresses Using a Beam-Based Elastic Foundation Bonded Joint Model
Efficient, semi-analytical models of bonded joints are utilized for initial joint design and sizing due to their convenience and speed. Many of these models are based on beam and plate theories, which are most applicable when in-plane stresses/strains dominate. While this can be a sensible assumption for obtaining the deformations of the joint, out of plane (transverse) stresses are often of critical importance for failure in bonded joints composed of fiber reinforced composite materials. Since through-thickness strains are neglected in these semi-analytical theories, the present study shows a method to back-calculate the out of plane stresses based on stress balance equations, which use the in-plane stresses and displacements that have already been obtained. The method was implemented within the Joint Element Designer (JED) software, and verification and validation examples have been shown. As is typical for these types of models, corner stress singularities are not captured by the JED model, but the general trends of the stress and deformation fields agreed with a higher fidelity finite element model. As such, this method for obtaining out of plane stresses, when coupled with the JED code, is very useful for the complete stress analysis of bonded composite joints.
composites↗
Involute Working Group – FSI Analysis of Fuel Plates Using Finite Volume and Finite Element Methods
The three involute plate research reactors RHF, HFIR, and FRM II have expressed an interest in using computational software to carry their steady-state safety analysis. Since these tools represent a significant departure from the methods used currently (one-dimensional), the acceptability of the new approach by regulators requires thorough verification and validation of these tools. Therefore, Argonne National Laboratory and the three involute-plate reactors formed an informal group called the Involute Working Group aiming at qualifying computational tools to perform steady-state safety analysis. The present report focuses on a comparison of finite volume and finite element methods to model solids in fluid-structure interaction problems with the goal to estimate the coolant flow-induced fuel plate deflections obtained with the two methods. The finite volume method will be obsoleted in STARCCM+ by the end of 2021, nevertheless, this evaluation is important because the method was used by ANL researchers to model the response of the fuel plates, despite its drawbacks, which are discussed in the report. It was essential to check how those estimates compare to the results obtained with the finite element method that is considered superior for structural analysis. Various geometries, i.e., flat, cylindrical and circle-involute fuel plates, as well as coolant flow speed, were considered. The comparison shows that, independently of the plate geometry, the finite volume method significantly underestimates the deflection as compared to finite element method for coarser meshes. When the discretization is developed as a result of a mesh sensitivity study using finite element method, the result obtained using finite volume method can be a few times smaller than the corresponding finite element method solution. A code-to-code comparison , between STAR-CCM+ and LS-DYNA was included in the analysis. Within the LS-DYNA models, two types of finite element formulations were used: solid and shell finite elements. Mesh sensitivity study showed that both approaches converge to a similar value that was obtained with STAR-CCM+ finite element solver. The evaluation of the computational solvers was extended by adding two benchmark cases from the STAR-CCM+ Verification Suite and presented in the Appendix A. The selected cases are: (1) bending of a cantilever beam under external load, and (2) cylindrical shell deformation analysis, known in the literature as ‘Scordelis-Lo roof’. The problems were solved with finite volume, and finite element methods, and the results confirmed the previously discussed findings. The analysis shows that the finite element solver is superior to the finite volume solver in terms of representation of model geometry and estimating the structural behavior of fuel plates. Depending on the ratio of the load to the flexibility of the plate, the finite volume solver can greatly under- or overestimate the structural response if a very carefully selected mesh is not used.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Binding of Phosphate Species to Ca 2+ and Mg 2+ in Aqueous Solution
Phosphate derivatives and their interaction with metal cations are involved in many important biological phenomena, so an accurate characterization of the phosphate-metal interaction is necessary to properly understand the role of phosphate-metal contacts in mediating biological function. Herein, we improved the standard 12-6 Lennard-Jones (LJ) potential via the usage of the 12-6-4 LJ model, which incorporates ion-induced dipole interactions. Via parameter scanning, we fine-tuned the 12-6-4 LJ polarizability values to obtain accurate absolute binding free energies for the phosphate anions H 2 PO 4 – , HPO 4 2– , PO 4 3– coordinating with Ca 2+ and Mg 2+ . First, we modified the phosphate 12-6-4 LJ parameters to reproduce the solvation free energies of the series of phosphate anions using the thermodynamic integration (TI) method. Then, using the potential mean force (PMF) method, the polarizability of the metal-phosphate interaction was obtained. We show that the free energy profiles of phosphate ions coordinated to Ca 2+ and Mg 2+ generally show similar trends at longer metal–phosphate distances, while the absolute binding energy values increased with deprotonation. The resulting parameters demonstrate the flexibility of the 12-6-4 LJ-type nonbonded model and its usefulness in accurately describing cation–anion interactions.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Leptonic cascade decays of a heavy Higgs boson through vectorlike leptons at the LHC
We demonstrate the potential of fully leptonic cascade decays of a heavy neutral Higgs boson through vectorlike leptons as a simultaneous probe for extended Higgs sectors and extra matter particles at the LHC. The processes we explore are unique in that their event topologies lead to di-boson-like leptonic final states with a lepton pair which does not reconstruct the mass of a gauge boson. By recasting existing $2\ell$ + $E^{\text{miss}}_{R}$ and $3/4\ell$ searches channels using run2 data from the LHC we obtain model independent bounds on the masses of heavy scalars and vectorlike leptons and use these results to explore future prospects at the HL-LHC. Our results can be directly applied to any kind of new physics scenarios sharing the final states and the event topology. For concreteness, we apply our results to a benchmark scenario: a two Higgs doublet model type-II augmented with vectorlike leptons. Remarkably, even with current data the sensitivity of our analysis shows a reach for masses of a heavy neutral Higgs and vectorlike leptons up to 2 TeV and 1.5 TeV, respectively. Even for low tan β ≳ 1, the analysis retains sensitivity to heavy Higgs masses slightly above 1 TeV. The future sensitivities at the HL-LHC extend the reach for heavy Higgses and new leptons to 2.7 TeV and 2 TeV, respectively.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
A High-Resolution X-Ray and Optical Study of SN1006: Asymmetric Expansion and Small-Scale Structure in a Type Ia Supernova Remnant
We introduce a deep (670 ks) X-ray survey of the entire SN 1006 remnant from the Chandra X-Ray Observatory, together with a deep Hα image of SN 1006 from the 4 m Blanco telescope at CTIO. Comparison with Chandra images from 2003 gives the first measurement of the X-ray proper motions around the entire periphery, carried out over a 9 yr baseline. We find that the expansion velocity varies significantly with azimuth. The highest velocity of approx.7400 km/s (almost 2.5 times that in the northwest (NW)) is found along the southeast (SE) periphery, where both the kinematics and the spectra indicate that most of the X-ray emission stems from ejecta that have been decelerated little, if at all. Asymmetries in the distribution of ejecta are seen on a variety of spatial scales. Si-rich ejecta are especially prominent in the SE quadrant, while O and Mg are more uniformly distributed, indicating large-scale asymmetries arising from the explosion itself. Neon emission is strongest in a sharp filament just behind the primary shock along the NWrim, where the pre-shock density is highest. Here the Ne is likely interstellar, while Ne within the shell may include a contribution from ejecta. Within the interior of the projected shell we find a few isolated "bullets" of what appear to be supernova ejecta that are immediately preceded by bowshocks seen in Hα, features that we interpret as ejecta knots that have reached relatively dense regions of the surrounding interstellar medium, but that appear in the interior in projection. Recent three-dimensional hydrodynamic models for Type Ia supernovae display small-scale features that strongly resemble the ones seen in X-rays in SN 1006; an origin in the explosion itself or from subsequent hydrodynamic instabilities both remain viable options. We have expanded the search for precursor X-ray emission ahead of a synchrotron-dominated shock front, as expected from diffusive shock acceleration theory, to numerous regions along both the northeast and southwest rims of the shell. Our data require that a precursor be thinner than about 3, and fainter than about 5% of the post-shock peak. These limits suggest that the magnetic field is amplified by a factor of seven or more in a narrow precursor region, promoting diffusive particle acceleration.
galaxies: active↗
Tank Tests of a 1/7-Size Dynamic Model of the Grumman XJR2F-1 Amphibian to Determine the Effect of Slotted- and Split-Type Flaps on Take-Off Stability - NACA Model 212, TED No. NACA 2378
Additional tests of a 1/7-size model of the Grumman XJR2F-1 amphibian were made in Langley tank no. 1 to compare the behavior during take-off of the model equipped with split- and slotted-type flaps. The slotted flag had a large effect on locating the forward center-of-gravity limits for stable take-offs. Stable take-offs within the normal operating range of positions of the center of gravity could be made with the split flaps deflected 45deg or with the slotted flaps deflected less than 20deg. At flap deflections required for similar take-off stability, the use of split-flaps resulted lower take-off speeds than the use of slotted flaps. An increase in forward acceleration from 1.1 to 4.8 feet per second per second moved the center-of-gravity limit forward approximately 3-percent mean aerodynamic chord.
Land, Norman S.↗
Sensitivity of Spruce/Moss Boreal Forest Net Ecosystem Productivity to Seasonal Anomalies in Weather
Abstract. A process-oriented, daily time step model of a spruce/moss boreal ecosystem simulated 1994 and 1995 productivity for a Boreal Ecosystem-Atmosphere Study site near Thompson, Manitoba. Simulated black spruce net primary productivity (NPP) was 139 g C m(exp -2) in 1994 and 112 in 1995; feathermoss NPP was 13.0 g C m(exp -2) in 1994 and 9.7 in 1995; decomposition was 126 g C m(exp -2) in 1994 and 130 in 1995; net ecosystem productivity (NEP) was an uptake of 26.3 g C m(exp -2)in 1994 and 2.5 in 1995. A very dry period for the first half of the 1995 summer was the major cause of that year's lower productivity. Sensitivity simulations explored the impact of 2-month long warmer, cooler, wetter, and drier spells on ecosystem productivity. Warmer summers decreased spruce NPP, moss NPP, and NEP; cooler summers had the opposite effect. Earlier snowmelt (due to either warmer spring temperatures or reduced winter precipitation) increased moss and spruce NPP; later snowmelt had the opposite effect. The largest effect on decomposition was a 5% reduction due to a drier summer. One-month droughts (April through October) were also imposed on 1975 base year weather. Early summer droughts reduced moss annual NPP by -30-40%; summer droughts reduced spruce annual NPP by 10%; late summer droughts increased moss NPP by about 20% due to reduced respiration; May to September monthly droughts reduced heterotrophic respiration by about 10%. Variability in NEP was up to roughly +/- 35%. Finally, 1975 growing season precipitation was redistributed into frequent, small rainstorms and infrequent, large rainstorms. These changes had no effect on spruce NPP. Frequent rainstorms increased decomposition by a few percent, moss NPP by 50%, and NEP by 20%. Infrequent rainstorms decreased decomposition by 5%, moss NPP by 50% and NEP by 15%. The impact of anomalous weather patterns on productivity of this ecosystem depended on their timing during the year. Multiyear data sets are necessary to understand this behavior and test these types of models.
Frolking, Steve↗
Machine learning-driven descriptions of protein dynamics at solid-liquid interfaces
This chapter has described how ML has enabled quantitative analysis of HS-AFM data to discover the physical phenomena governing protein dynamics and ordering at solid-liquid interfaces. The research detailed in this chapter modeled the rotation models of protein nanorods, the discovery of which would otherwise not be possible. By tracking the trajectories of individual protein rods from frame to frame, it was possible to model Brownian type motion and behaviors and Levy-flight dynamics that had not previously been shown. We also described the application of the Python package AtomAI, which has been developed specifically to analyze and extract physical phenomena, providing exemplar code for training an ensemble of deep neural networks to produce the semantic segmentation of AFM data and functions for encoding and decoding local environments. We last described a combinatorial approach to analyze very noisy data with a densely covered substrate where the emergence of order for the protein liquid crystals could be elucidated. By combining the methods from Case 1 and 2, it was possible to obtain the center of mass and angle for each rod in the images and track the assembly of the rods over time into a 2D liquid crystal array on the surface of mica.
protein dynamics, solid-liquid interfaces, atomic ↗
High-temperature chromium diffusion in austenitic stainless steel: Ab initio molecular dynamics simulations
Chromium self-diffusion through stainless steel (SS) matrix and along grain boundaries is an important mechanism controlling SS structural materials corrosion. For this work, Cr diffusion in austenitic SS was simulated using canonical ab initio molecular dynamics with realistic models of type-316 SS bulk, with and without Cr vacancies, and a low-energy Σ3 twin boundary typically observed at active corrosion sites. Cr self-diffusion coefficients at 750 and 850 °C calculated using Einstein’s diffusion equation are 4.2 × 10 –6 and 8.1 × 10 –6 Å 2 ps –1 in pristine bulk, 3.8 × 10 –3 and 5.5 × 10 –3 Å 2 ps –1 in bulk including Cr vacancies, and 9.5 × 10 –2 and 1.0 × 10 –1 Å 2 ps –1 at a Σ3[1 1 1]60° twin boundary.
36 MATERIALS SCIENCE↗
Charging needs for electric semi-trailer trucks
Battery-electric vehicles provide a pathway to decarbonize heavy-duty trucking, but the market for heavy-duty battery-electric semi-trailer trucks is nascent, and specific charging requirements remain uncertain. We leverage large-scale vehicle telematics data (>205 million miles of driving) to estimate the charging behaviors and infrastructure requirements for U.S. battery-electric semi-trailer trucks within three operating segments: local, regional, and long-haul. We model two types of charging - mid-shift (fast) and off-shift (slow) - and show that off-shift charging at speeds compatible with current light-duty charging infrastructure (i.e., =350 kW) can supply 35% to 77% of total energy demand for local and regional trucks with =300-mile range. Megawatt-level speeds are required for mid-shift charging, which make up 44% to 57% of energy demand for long-haul trucks with =500-mile range. However, demand shifts from mid-shift to off-shift charging as the range for battery-electric trucks increases and when off-shift charging is widely available. Finally, we observe geographic trends in charging demand, finding that local trucks have greater demand within urban areas, whereas long-haul trucks have more demand along rural interstate corridors. As the range for battery-electric trucks increases, we show that charging demand shifts from rural to urban locations due to observed vehicle dwell tendencies.
33 ADVANCED PROPULSION SYSTEMS↗
Quantum bath augmented stochastic nonequilibrium atomistic simulations for molecular heat conduction
Classical molecular dynamics (MD) has been shown to be effective in simulating heat conduction in certain molecular junctions since it inherently takes into account some essential methodological components which are lacking in the quantum Landauer-type transport model, such as many-body full force-field interactions, anharmonicity effects and nonlinear responses for large temperature biases. However, the classical MD reaches its limit in the environments where the quantum effects are significant (e.g. with low-temperatures substrates, presence of extremely high frequency molecular modes). Here, we present an atomistic simulation methodology for molecular heat conduction that incorporates the quantum Bose–Einstein statistics into an “effective temperature” in the form of a modified Langevin equation. We show that the results from such a quasi-classical effective temperature MD method deviates drastically when the baths temperature approaches zero from classical MD simulations and the results converge to the classical ones when the bath approaches the high-temperature limit, which makes the method suitable for full temperature range. In addition, we show that our quasi-classical thermal transport method can be used to model the conducting substrate layout and molecular composition (e.g. anharmonicities, high-frequency modes). Anharmonic models are explicitly simulated via the Morse potential and compared to pure harmonic interactions to show the effects of anharmonicities under quantum colored bath setups. Finally, the chain length dependence of heat conduction is examined for one-dimensional polymer chains placed in between quantum augmented baths.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Geometrical frustration versus Kitaev interactions in BaCo 2 (AsO 4 ) 2
Recently, Co-based honeycomb magnets have been proposed as promising candidate materials to host the Kitaev spin liquid (KSL) state. One of the front-runners is BaCo 2 (AsO 4 ) 2 (BCAO), where it was suggested that the exchange processes between Co 2+ ions via the surrounding edge-sharing oxygen octahedra could give rise to bond-dependent Kitaev interactions. In this work, we present and analyze a comprehensive inelastic neutron scattering (INS) study of BCAO with fields in the honeycomb plane. Combining the constraints from the magnon excitations in the high-field polarized state and the inelastic spin structure factor measured in zero magnetic field, we examine two leading theoretical models: the Kitaev-type JK Γ Γ ′ model and the XXZ - J 1 - J 3 model. We show that the existing experimental data can be consistently accounted for by the XXZ - J 1 - J 3 model but not by the JK Γ Γ ′ model, and we discuss the implications of these results for the realization of a spin liquid phase in BCAO and more generally for the realization of the Kitaev model in cobaltates.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗