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At least 1,315 records · Page 73

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials

Here, we present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs), and disordered Zr-oxides. Five MLIP architectures (MACE, NequIP, Allegro, MTP, and Torch-ANI) are trained and tested, focusing not only on traditional metrics (energies, forces, and stresses) but also explicitly validating derived physical observables such as lattice constants, volumes, and reaction barriers. We find that most models reach comparable accuracy on standard error metrics across the simple systems, although equivariant MLIPs offer 1.5–2× improvements over nonequivariant MLIPs in energy and force error for structurally complex or compositionally disordered environments such as HEAs and Zr–O systems. Our analysis highlights that low errors in energy and force predictions do not guarantee reliable observables, emphasizing the necessity of explicit validation. We demonstrate limitations in cross-framework transferability, as models trained on one zeolite framework (CHA) fail to reliably generalize to predictions of structurally distinct frameworks (e.g., MFI). Size-extensive tests show some dependence on system size for MgO, resulting from forced periodicity. The HEA and Zr–O data sets are identified as challenging tests for future benchmarks and MLIP model architecture developments as they show significant differentiation in error between MLIP architectures and are still relatively difficult at 1000 training images. Moving forward, we recommend that benchmarking efforts shift their focus from marginal accuracy improvements in energy and force errors toward identifying and understanding model failure modes, rigorously assessing transferability, and evaluating how their errors affect observable predictions. For researchers looking to choose an MLIP architecture, we suggest selecting equivariant MLIP architectures if the complexity of the system is a challenge. For simple materials problems, auxiliary features such as integration with molecular dynamics engines, trade-offs between computational data set generation cost vs MLIP inference speed, and framework integration may play a more important decision factor than small differences in error metrics that are unlikely to matter for production-level research.

chemical structure↗

Emergence of Topologically Nontrivial Spin-Polarized States in a Segmented Linear Chain

The synthesis of new materials with novel or useful properties is one of the most important drivers in the fields of condensed matter physics and materials science. Discoveries of this kind are especially significant when they point to promising future basic research and applications. Van der Waals bonded materials comprised of lower-dimensional building blocks have been shown to exhibit emergent properties when isolated in an atomically thin form. Here, we report the discovery of a transition metal chalcogenide in a heretofore unknown segmented linear chain form, where basic building blocks each consisting of two hafnium atoms and nine tellurium atoms (Hf 2 Te 9 ) are van der Waals bonded end-to-end. First-principle calculations based on density functional theory reveal striking crystal-symmetry-related features in the electronic structure of the segmented chain, including giant spin splitting and nontrivial topological phases of selected energy band states. In this work, atomic-resolution scanning transmission electron microscopy reveals single segmented Hf 2 Te 9 chains isolated within the hollow cores of carbon nanotubes, with a structure consistent with theoretical predictions. Van der Waals-bonded segmented linear chain transition metal chalcogenide materials could open up new opportunities in low-dimensional, gate-tunable, magnetic and topological crystalline systems.

36 MATERIALS SCIENCE↗

Unconventional Wells Interference: Supervised Machine Learning for Detecting Fracture Hits

The primary objective of the study was development of a machine learning (ML)-based workflow for fracture hit (“frac hit”) detection and monitoring using shale oil-field data such as drilling surveys, production history (oil and produced water), pressure, and fracking start time and duration records. The ML method takes advantage of long short-term memory (LSTM) and multilayer perceptron (MLP) neural networks to identify the frac hits due to hydraulic communication between the fracking child well(s) and the producing parent well(s) within the same pad (intra-pad interaction) and/or on different pads (inter-pad interaction). It utilizes time series of pressure and production data from within a pad and from adjacent pads. The workflow can capture time variable features of frac hits when the model architecture is deep and wide enough, with enough trainable parameters for deep learning and feature extraction, as demonstrated in this paper by using training and testing subsets of the field data from selected neighboring pads with over a couple of hundred wells. The study was focused on frac-hit interaction among paired wells and demonstrated that the ML model, once trained, can predict the frac-hit probability.

58 GEOSCIENCES↗

Modeling Assessment of Tidal Energy Extraction in the Western Passage

Numerical models have been widely used for the resource characterization and assessment of tidal instream energy. The accurate assessment of tidal stream energy resources at a feasibility or project-design scale requires detailed hydrodynamic model simulations or high-quality field measurements. This study applied a three-dimensional finite-volume community ocean model (FVCOM) to simulate the tidal hydrodynamics in the Passamaquoddy–Cobscook Bay archipelago, with a focus on the Western Passage, to assist tidal energy resource assessment. IEC Technical specifications were considered in the model configurations and simulations. The model was calibrated and validated with field measurements. Energy fluxes and power densities along selected cross sections were calculated to evaluate the feasibility of the tidal energy development at several hotspots that feature strong currents. When taking both the high current speed and water depth into account, the model results showed that the Western Passage has great potential for the deployment of tidal energy farms. The maximum extractable power in the Western Passage was estimated using the Garrett and Cummins method. Different criteria and methods recommended by the IEC for resource characterization were evaluated and discussed using a sensitivity analysis of energy extraction for a hypothetical tidal turbine farm in the Western Passage.

16 TIDAL AND WAVE POWER↗

A spectral reflectance estimation technique using multispectral data from the Viking lander camera

A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.

Park, S. K.↗

Extended performance solar electric propulsion thrust system study. Volume 4: Thruster technology evaluation

Several thrust system design concepts were evaluated and compared using the specifications of the most advanced 30 cm engineering model thruster as the technology base. Emphasis was placed on relatively high power missions (60 to 100 kW) such as a Halley's comet rendezvous. The extensions in thruster performance required for the Halley's comet mission were defined and alternative thrust system concepts were designed in sufficient detail for comparing mass, efficiency, reliability, structure, and thermal characteristics. Confirmation testing and analysis of thruster and power processing components were performed, and the feasibility of satisfying extended performance requirements was verified. A baseline design was selected from the alternatives considered, and the design analysis and documentation were refined. The baseline thrust system design features modular construction, conventional power processing, and a concentrator solar array concept and is designed to interface with the Space Shuttle.

Poeschel, R. L.↗

Extended performance solar electric propulsion thrust system study. Volume 2: Baseline thrust system

Several thrust system design concepts were evaluated and compared using the specifications of the most advanced 30- cm engineering model thruster as the technology base. Emphasis was placed on relatively high-power missions (60 to 100 kW) such as a Halley's comet rendezvous. The extensions in thruster performance required for the Halley's comet mission were defined and alternative thrust system concepts were designed in sufficient detail for comparing mass, efficiency, reliability, structure, and thermal characteristics. Confirmation testing and analysis of thruster and power-processing components were performed, and the feasibility of satisfying extended performance requirements was verified. A baseline design was selected from the alternatives considered, and the design analysis and documentation were refined. The baseline thrust system design features modular construction, conventional power processing, and a concentractor solar array concept and is designed to interface with the space shuttle.

Poeschel, R. L.↗

Computer image processing in marine resource exploration

Pictographic data or imagery is commonly used in marine exploration. Pre-existing image processing techniques (software) similar to those used on imagery obtained from unmanned planetary exploration were used to improve marine photography and side-scan sonar imagery. Features and details not visible by conventional photo processing methods were enhanced by filtering and noise removal on selected deep-sea photographs. Information gained near the periphery of photographs allows improved interpretation and facilitates construction of bottom mosaics where overlapping frames are available. Similar processing techniques were applied to side-scan sonar imagery, including corrections for slant range distortion, and along-track scale changes. The use of digital data processing and storage techniques greatly extends the quantity of information that can be handled, stored, and processed.

Paluzzi, P. R.↗

Program review presentation to Level 1, Interagency Coordination Committee

Progress in the development of crop inventory technology is reported. Specific topics include the results of a thematic mapper analysis, variable selection studies/early season estimator improvements, the agricultural information system simulator, large unit proportion estimation, and development of common features for multi-satellite information extraction.

Source record↗

Classification of cryocoolers

A great diversity of methods and mechanisms were devised to effect cryogenic refrigeration. The basic parameters and considerations affecting the selection of a particular system are reviewed. A classification scheme for mechanical cryocoolers is presented. An important distinguishing feature is the incorporation or not of a regenerative heat exchanger, of valves, and of the method for achieving a pressure variation.

Walker, G.↗

Research in remote sensing of vegetation

The research topics undertaken were primarily selected to further the understanding of fundamental relationships between electromagnetic energy measured from Earth orbiting satellites and terrestrial features, principally vegetation. Vegetation is an essential component in the soil formation process and the major factor in protecting and holding soil in place. Vegetation plays key roles in hydrological and nutrient cycles. Awareness of improvement or deterioration in the capacity of vegetation and the trends that those changes may indicate are, therefore, critical detections to make. A study of the relationships requires consideration of the various portions of the electromagnetic spectrum; characteristics of detector system; synergism that may be achieved by merging data from two or more detector systems or multiple dates of data; and vegetational characteristics. The vegetation of Oregon is sufficiently diverse as to provide ample opportunity to investigate the relationships suggested above several vegetation types.

Schrumpf, Barry J.↗

A strategy for space biology and medical science for the 1980s and 1990s

A guideline is provided for developing NASA's long-term mission plans and a rational, coherent research program. Ten topical areas for research are addressed: developmental biology, gravitropism in plants, sensorimotor integration, bone and mineral metabolism, cardiovascular/pulmonary function, muscle remodeling, nutrition, human reproduction, space anemia, and human behavior. Scientific goals, objectives, and required measurements and facilities for each of the major areas of space biology and medicine are identified and described along with primary goals and objectives for each of these disciplines. Proposals are made concerning the use of scientific panels to oversee the implementation of the strategy, life sciences' need for continuous access to spaceflight opportunities, the advantages of a focused mission strategy, certain design features that will enhance spaceflight experimentation, and general facilities. Other topics that are considered include mission planning, crew selection and training, and interagency and international cooperation.

Source record↗

The Chemical Basis for the Origin of the Genetic Code and the Process of Protein Synthesis

A model for the origin of protein synthesis. The essential features of the model are that 5'-AMP and perhaps other monoribonucleotides can serve as catalysts for the selective synthesis of L-based peptides. A unique set of characteristics of 5'-AMP is responsible for the selective catalysts and these characteristics are described in detail. The model involves the formation of diesters as intermediates and selectivity for use of the L-isomer occurs principally at the step of forming the diester. However, in the formation of acetyl phenylalanine-AMP monoester there is a selectivity for esterification by the D-isomer. Data showing this selectivity is presented. This selectivity for D-isomer disappears after the first step. The identity was confirmed of all four of possible diesters of acetyl-D- and -L phenylaline with 5'-AMP by nuclear magnetic resonance (NMR). The data using flourescence and NMR show the Trp ring can associate with the adenine ring more strongly when the D-isomer is in the 2' position than it can when in the 3' position. These same data also suggest a molecular mechanisim for the faster esterificaton of 5'-AMP by acetyl-D-phenylaline. Some new data is also presented on the possible structure of the 2' isomer of acetyl-D-tryptophan-AMP monoester. The HPLC elution times of all four possible acetyl diphenylalanine esters of 5'-AMP were studied, these peptidyl esters will be products in the studies of peptide formation on the ribose of 5'-AMP. Other studies were on the rate of synthesis and the identity of the product when producing 3'Ac-Phe-2'tBOC-Phe-AMP diester. HPLC purification and identification of this product were accomplished.

Lacey, James C., Jr.↗

A generalized gamma(s)-family of self-starting algorithms for computational structural dynamics

A generalized gamma(s)-family of self-starting single-step formulations are presented in order to provide simplified yet effective dynamic attributes to include features towards eliminating the need to involve accelerations in the computational process for structural dynamic problems. By appropriately selecting the parameters pertaining to gamma(s)(s = 1, 2, 3), both explicit and implicit formulations are obtained. The stability and accuracy characteristics of the gamma(s)-family of representations are presented to validate the robustness of the formulations for structural dynamic problems. Numerous illustrative examples are described and the results are in excellent agreement and validate the applicability of these formulations for structural dynamic computations.

Namburu, Raju R.↗

Searching for patterns in remote sensing image databases using neural networks

We have investigated a method, based on a successful neural network multispectral image classification system, of searching for single patterns in remote sensing databases. While defining the pattern to search for and the feature to be used for that search (spectral, spatial, temporal, etc.) is challenging, a more difficult task is selecting competing patterns to train against the desired pattern. Schemes for competing pattern selection, including random selection and human interpreted selection, are discussed in the context of an example detection of dense urban areas in Landsat Thematic Mapper imagery. When applying the search to multiple images, a simple normalization method can alleviate the problem of inconsistent image calibration. Another potential problem, that of highly compressed data, was found to have a minimal effect on the ability to detect the desired pattern. The neural network algorithm has been implemented using the PVM (Parallel Virtual Machine) library and nearly-optimal speedups have been obtained that help alleviate the long process of searching through imagery.

Paola, Justin D.↗

Thermal barrier coatings issues in advanced land-based gas turbines

The Department of Energy's Advanced Turbine Systems (ATS) program is aimed at fostering the development of a new generation of land-based gas turbine systems with overall efficiencies significantly beyond those of current state-of-the-art machines, as well as greatly increased times between inspection and refurbishment, improved environmental impact, and decreased cost. The proposed duty cycle of ATS machines will emphasize different criteria in the selection of materials for the critical components. In particular, thermal barrier coatings (TBC's) will be an essential feature of the hot gas path components in these machines. In fact, the goals of the ATS will require significant improvements in TBC technology, since these turbines will be totally reliant on TBC's, which will be required to function on critical components such as the first stage vanes and blades for times considerably in excess of those experienced in current applications. Issues that assume increased importance are the mechanical and chemical stability of the ceramic layer and of the metallic bond coat; the thermal expansion characteristics and compliance of the ceramic layer; and the thermal conductivity across the thickness of the ceramic layer. Obviously, the ATS program provides a very challenging opportunity for TBC's, and involves some significant opportunities to extend this technology. A significant TBC development effort is planned in the ATS program which will address these key issues.

Parks, William P.↗