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Since shortly after launch the radiometric performance of band 6 of the ETM+ instrument on Landsat 7 has been evaluated using vicarious calbiration techniques for both land and water targets. This evaluation indicates the radiometric performance of band 6 has been both highly stable and accurate.
The performance of the transition layer in a Cu/Al composite casting directly affects the quality of subsequent plastic deformation processing; however, there are no universal or standardized measurement indices for the performance of the transition layer. In this study, Cu/Al composite castings were prepared using the pouring aluminum method, and the resulting solidification microstructures on the bending resistance were investigated. The results of this study lay a theoretical foundation for the development of the plastic processing technologies of these composite castings. A thinner transition layer in the Cu/Al composite casting led to improved bending resistance. In addition, for a fixed total thickness of the transition layer, the bending resistance was mainly controlled by the γ/β interface and β + eutectic (α + β) microstructure, and the thickness of the γ phase had a negligible effect on the bending resistance. The γ/β interface cracked first when the transition layer bore the tensile and shear stress during the bending process, which resulted in the transition layer easily separating from the copper. The bending resistance of the transition layer can be feasibly judged by measuring the bending angle of the specimen tip, which can be easily performed when the specimen bends toward the aluminum direction, suggesting that our proposed method has considerable practical significance.
The adoption of any binder system for structural concrete depends on the performance characteristics desired for addressing the long-term deformation and durability concerns. The major properties influencing the performance includes the shrinkage characteristics governing the long-term deformation, and durability characteristics related to various transport mechanisms, governing the performance in different service conditions. This paper describes the potential of Limestone Calcined Clay Cement (LC{sup 3}) for use in structural concrete in comparison with Ordinary Portland Cement (OPC) and fly ash based blended cement (FA30). Three types of concrete mixtures were designed for the study, two based on achieving an equivalent strength grade (M30 and M50 concrete grade) with each binder, and the third with equal binder content and w/b ratio. Mechanical properties such as compressive strength and elastic modulus, and autogenous and drying shrinkage, along with various durability parameters of the different concretes were assessed. Oxygen permeability, rapid chloride penetration, chloride migration, resistivity development and water sorptivity were the various parameters considered for evaluation of durability performance. The results indicate the superiority of LC{sup 3} binder over other binders in producing durable concrete, especially in a chloride laden environment. The major reason for the better performance was attributed to the more compact and dense microstructure of the system with the LC{sup 3} binder against OPC and FA30. The drying shrinkage performance was seen to be similar for concrete with all three binders.
Experimental results for fuel consumption and emissions are presented for a 350 CID (5.7 liter) Chevrolet V-8 engine modified for lean operation with gasoline. The lean burn engine achieved peak thermal efficiency at an equivalence ratio of 0.75 and a spark advance of 60 deg BTDC. At this condition the lean burn engine demonstrated a 10% reduction in brake specific fuel consumption compared with the stock engine; however, NOx and hydrocarbon emissions were higher. With the use of spark retard and/or slightly lower equivalence ratios, the NOx emissions performance of the stock engine was matched while showing a 6% reduction in brake specific fuel consumption. Hydrocarbon emissions exceeded the stock values in all cases. Diagnostic data indicate that lean performance in the engine configuration tested is limited by ignition delay, cycle-to-cycle pressure variations, and cylinder-to-cylinder distribution.
It is proposed that humans in automated systems will be asked to assume the role of troubleshooter or problem solver and that the problems which they will be asked to solve in such systems will not be amenable to rote solution. The design of visual displays for problem solving in such situations is considered, and the results of two experimental investigations of human problem solving performance in the diagnosis of faults in graphically displayed network problems are discussed. The effects of problem size, forced-pacing, computer aiding, and training are considered. Results indicate that human performance deviates from optimality as problem size increases. Forced-pacing appears to cause the human to adopt fairly brute force strategies, as compared to those adopted in self-paced situations. Computer aiding substantially lessens the number of mistaken diagnoses by performing the bookkeeping portions of the task.
The development of a biaxial extensometer capable of measuring axial, torsion, and diametral strains to near-microstrain resolution at elevated temperatures is discussed. An instrument with this capability was needed to provide experimental support to the development of viscoplastic constitutive models. The advantages gained when torsional loading is used to investigate inelastic material response at elevated temperatures are highlighted. The development of the biaxial extensometer was conducted in two stages. The first involved a series of bench calibration experiments performed at room temperature. The second stage involved a series of in-place calibration experiments conducted at room and elevated temperature. A review of the calibration data indicated that all performance requirements regarding resolution, range, stability, and crosstalk had been met by the subject instrument over the temperature range of interest, 21 C to 651 C. The scope of the in-place calibration experiments was expanded to investigate the feasibility of generating stress relaxation data under torsional loading.
The effects of precipitation on wind turbine power output was analyzed. The tests were conducted on the two bladed Mod-0 horizontal axis wind turbine with three different rotor configurations. Experimental data from these tests are presented which clearly indicate that the performance of the Mod-0 wind turbine is affected by rain. Light rainfall degraded performance by as much as 20 percent while heavy rainfall degraded performance by as much as 30 percent. Snow mixed with drizzle degraded performance by as much as 36 percent at low windspeeds. Also presented are the results of an analysis to predict the effect of rain on wind turbine performance. This analysis used a blade element/momentum code with modified airfoil characteristics to account for the effect of rain and predicted a loss in performance of 31 percent in high winds with moderate rainfall rates. These predicted results agreed well with experimental data.
The transonic performance of a dual-throat, single-expansion-ramp nozzle (SERN) was investigated with a PARC computational fluid dynamics (CFD) code, an external flow Navier-Stokes solver. The nozzle configuration was from a conceptual Mach 5 cruise aircraft powered by four air-breathing turboramjets. Initial test cases used the two-dimensional version of PARC in Euler mode to investigate the effect of geometric variation on transonic performance. Additional cases used the two-dimensional version in viscous mode and the three-dimensional version in both Euler and viscous modes. Results of the analysis indicate low nozzle performance and a highly three-dimensional nozzle flow at transonic conditions. In another comparative study using the PARC code, a single-throat SERN configuration for which experimental data were available at transonic conditions was used to validate the results of the over/under turboramjet nozzle.
A computer study was performed to assess the accuracy of three brake pressure-torque mathematical models. The investigation utilized one main gear wheel, brake, and tire assembly of a McDonnell Douglas DC-9 series 10 airplane. The investigation indicates that the performance of aircraft antiskid braking systems is strongly influenced by tire characteristics, dynamic response of the antiskid control valve, and pressure-torque response of the brake. The computer study employed an average torque error criterion to assess the accuracy of the models. The results indicate that a variable nonlinear spring with hysteresis memory function models the pressure-torque response of the brake more accurately than currently used models.
Tests were performed on two spiral bevel gear sets in the NASA Glenn Spiral Bevel Gear Fatigue Test Rig to simulate the fielded failures of spiral bevel gears installed in a helicopter. Gear sets were tested until damage initiated and progressed on two or more gear or pinion teeth. During testing, gear health monitoring data was collected with two different health monitoring systems. Operational parameters were measured with a third data acquisition system. Tooth damage progression was documented with photographs taken at inspection intervals throughout the test. A software tool was developed for fusing the operational data and the vibration based gear condition indicator (CI) data collected from the two health monitoring systems. Results of this study illustrate the benefits of combining the data from all three systems to indicate progression of damage for spiral bevel gears. The tool also enabled evaluation of the effectiveness of each CI with respect to operational conditions and fault mode.
Alkali-silica reaction (ASR) causes concrete degradation, leading to cracking, rebar corrosion, and reduced structural integrity, which raises safety concerns. Ultrasonic nondestructive evaluation (NDE) effectively assesses concrete properties and monitors ASR progression. However, its deployment and analysis require specialized expertise and subjective interpretation. As computational power increases, artificial intelligence (AI) and machine learning (ML) algorithms are increasingly being used to automate NDE data analysis across various industries for AI-assisted automation. Regulatory agencies are adapting to this technological shift, prompting a need to evaluate current ML technologies’ capabilities and limitations in assessing concrete material properties and damage. This report presents a comparative analysis of four ML regression models for predicting concrete material damage induced by ASR expansion using long-term ultrasonic data monitoring. The models investigated include linear regression (LR), support vector regression (SVR), shallow neural networks (NN), and deep neural networks (DNN). LR, SVR, and shallow NN models use features extracted from ultrasonic signals, whereas the DNN model processes time-domain ultrasonic signals and frequency spectra directly. The study systematically compared the models’ performance from various perspectives, including model input, prediction performance, and generalization ability. The findings indicate significant variability in model performance, with some ML algorithms achieving very high or very low prediction accuracy depending on the preprocessing and feature engineering (extraction and selection) applied. Key insights include the observation that shallow ML models (LR, SVR, and shallow NNs) require meticulous preprocessing and feature extraction to achieve high accuracy. In contrast, the DNN model, although it bypasses the need for feature engineering, necessitates extensive preprocessing to mitigate noise and computational demands. The SVR model emerged as the top performer among the shallow models, and the DNN model exhibited superior performance on specific datasets but struggled with generalization across specimens from different batches. Additionally, the SVR model is sensitive to temperature variations, whereas the DNN model is robust in this regard. Using recurrent neural networks is recommended for future ASR expansion prediction studies. Recurrent neural networks’ inherent ability to capture temporal dependencies and long-term patterns makes them well suited for analyzing sequential ultrasonic monitoring data. Overall, the results and conclusions of this study could provide insights into the capabilities and effectiveness of ML when applied to ultrasonic NDE data and help identify best practices for using ML for ultrasonic NDE of concrete material properties.
Preliminary evaluations of limited cross beam data taken with the rebuilt optical cross beam units at the Gun Barrel Hill Test Site of ESSA are presented. The evaluations were made using the analogue Princeton Time Correlator. A study of these evaluations indicates that the rebuilt units are performing satisfactorily. However, there are indications that, in order to obtain useful information from the cross-correlations, it is essential to make judicious choices of computation time and frequency band pass filtering for the analysis of the data.
Thermoregulation in the space environment is critical for survival, especially in off- nominal operations. In such cases, mathematical models of thermoregulation are frequently employed to evaluate safety-of-flight issues in various human mission scenarious. In this study, the 225-node Wissler model and the 41-Node Metabolic Man model are employed to evaluate the effects of such a scenario. Metabolic loads on astronauts wearing the advanced crew escape suit (ACES) and liquid cooled ventilation garment (LCVG) are imposed on astronauts exposed to elevated cabin temperatures resulting from a systems failure. The study indicates that the performance of the ACES/LCVG cooling system is marginal. Increases in workload and or cabin temperature above nominal will increase rectal temperature, stored heat load, heart rate, and sweating, which could lead to deficits in the performance of cognitive and motor tasks. This is of concern as the ACES/LCVG is employed during Shuttle decent when the likelihood of a safe landing may be compromised. The study indicates that the most effective mitigation strategy would be to decrease the LCVG inlet temperature.
An initial review of the roughness data from the BOLT II flight is provided. The BOLT II roughness experiment was designed to investigate discrete trips in flight based on the diamond configuration, which has been shown to be an efficient vortex generator and boundary layer trip from extensive ground-based testing. There were three trip locations chosen for the flight test and their size (height and width) were tailored to the local boundary layer thickness, but all three were expected to trip at the same time or flight condition. Details about the flight vehicle design, instrumentation, and best estimated trajectory are discussed. The present paper is limited to only a review and analysis of the thermocouple data. Boundary layer transition onset times are derived from the thermocouple analysis, thus allowing an initial assessment of the performance of these discrete trips. Since the three trips were sized to trip the boundary layer at the same time, based on a previous wind tunnel study, the present analysis indicates that they performed as expected.
Chemicals released into the environment from historical activities at Los Alamos National Laboratory are still present in surface water and groundwater. In streams, which are mostly ephemeral on Laboratory land, chemicals tend to bind to sediment and are transported downstream via entrainment in storm water runoff during precipitation events. In several watersheds across the Laboratory, sediment transport mitigations have been installed to stymie the movement of contaminated sediments. These mitigations include: grade-control structures, sediment detention basins, riparian and in-channel vegetation plantings, wetland restoration and promotion, and vegetative buffers. These mitigations have been implemented with the overall goals of minimizing the potentially erosive nature of storm water runoff, enhancing deposition of sediment, and reducing access of contaminated sediments to storm water. These mitigations are monitored using stream gaging stations, precipitation gaging stations, and storm water sampling, including monitoring locations that bound the mitigation sites. Stage height/discharge is monitored at 5 minute intervals at a series of gaging stations. Precipitation data are collected across the Laboratory by means of 5 meteorological towers and an extended network of 14 precipitation gages. Sampling for analytical suites specific to each reach of the watershed is conducted using portable automated samplers. Sampling equipment and the extended rain gage network are deactivated during the winter/spring months (December to May) and reactivated in the summer/fall months (June to November) to capture monsoonal precipitation events and associated streamflow and to avoid damage to the equipment. Attenuation of flow and associated sediment transport are primary goals of the sediment transport mitigation activities. Decreasing flow velocity allows for increased infiltration, thus reducing peak discharge, reducing the distance the flood bore travels downstream, and reducing the distance suspended sediment and associated contaminants entrained in the storm water travel downstream. Data analyses of flow and suspended sediment concentrations performed over the past seven years indicate that these mitigations are performing as designed. (authors)
Functionalization of flexible materials based on mesoscopic reconstruction is a key strategy in fabricating biocompatible flexible electronics. This work is to acquire new mesoscopic bioelectronic hybrid materials of silk fibroin (SF)-Ag nanoclusters (AgNCs@BSA; BSA: bovine serum albumin), which enhance significantly the performance of silk memristors. It is to build AgNCs@BSA into SF mesoscopic networks by templated ß-crystallization. Atomic force microscopy potential probing indicates that AgNCs@BSA serve as electronic potential wells that change completely the transport behavior of charge particles within the SF films. This leads to significant enhancement in the switching speed (˜10 ns), very good switching stability, extremely low set/reset voltages (0.3/-0.18 V) of SF meso-hybrid memristors, compared with the original and other organic memristors, and displays unique synapse characteristics and the capability of synapse learning. Classical density functional theory Poisson–Nernst–Planck simulations indicate that the enhanced performance is subject to the low potential paths interconnecting the AgNCs@BSA, which guide charges' transport (Ag+) and deposition in SF films.
Here, recent work shows that strong stability and dimensionality freedom are essential for robust numerical integration of thermostatted ringpolymer molecular dynamics (T-RPMD) and path-integral molecular dynamics, without which standard integrators exhibit non-ergodicity and other pathologies [R. Korol et al., J. Chem. Phys. 151, 124103 (2019) and R. Korol et al., J. Chem. Phys. 152, 104102 (2020)]. In particular, the BCOCB scheme, obtained via Cayley modification of the standard BAOAB scheme, features a simple reparametrization of the free ring-polymer sub-step that confers strong stability and dimensionality freedom and has been shown to yield excellent numerical accuracy in condensed-phase systems with large time steps. Here, we introduce a broader class of T-RPMD numerical integrators that exhibit strong stability and dimensionality freedom, irrespective of the Ornstein–Uhlenbeck friction schedule. In addition to considering equilibrium accuracy and time step stability as in previous work, we evaluate the integrators on the basis of their rates of convergence to equilibrium and their efficiency at evaluating equilibrium expectation values. Within the generalized class, we find BCOCB to be superior with respect to accuracy and efficiency for various configuration-dependent observables, although other integrators within the generalized class perform better for velocity-dependent quantities. Extensive numerical evidence indicates that the stated performance guarantees hold for the strongly anharmonic case of liquid water. Both analytical and numerical results indicate that BCOCB excels over other known integrators in terms of accuracy, efficiency, and stability with respect to time step for practical applications.
Physical aging or degradation of amine-containing polymers and supported amine adsorbents is a critical issue that could limit practical application of such materials for CO 2 capture. However, to date, there is a scarcity of studies that evaluate the long-term stability of amine-based sorbents without the exclusive use of accelerated aging tests. Here, we demonstrate that extended aging (~2 years) of linear poly(propylenimine) (LPPI) confined in mesoporous silica (SBA-15) supports does not drastically impact the CO 2 adsorption performance under simulated flue gas (10% CO 2 ) and direct air capture (DAC, 400 ppm CO 2 ) conditions, although the behavior of the aged sorbents and polymers in the two CO 2 concentration regimes differs. Sorbents made with aged LPPI had modestly decreased CO 2 uptake performance (<~20% lower) compared to the fresh polymers, with overall good CO 2 cycling performance. The data indicate that only slow degradation occurs under the deployed ambient storage conditions. Even after extended aging, the LPPI-based sorbents preserved their ability to display stable temperature-swing cycling performance. In parallel, the impact of blending LPPI polymers of different number-average molecular weights, M n , is evaluated, seeking to understand its impact on adsorbent performance. We find that the results demonstrate that blends of two M n aged LPPI give similar CO 2 adsorption performance to adsorbents made from a single M n LPPI, suggesting that molecular weight will not negatively impact adsorbent performance in the studied M n range. After an accelerated oxidation experiment, the aged LPPI sorbents retained a larger portion of the samples’ original performance when cycling under simulated flue gas conditions than under DAC conditions. However, in each case, the oxidized sorbents could be cycled repeatedly with consistent uptake performance. Overall, these first of their kind extended aging tests suggest that LPPI-based amine adsorbents offer promise for long term, stable use in carbon capture applications.