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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Lessons learnt from post EIS evaluations of national road schemes in Ireland

The Irish National Roads Authority (NRA) recently completed over twenty post environmental impact assessment evaluations of noise chapters prepared as part of Environmental Impact Statements (EISs) for new national road schemes in Ireland. The study focused on a range of issues including a review of noise monitoring procedures, noise prediction methodologies and an assessment of the effectiveness of noise mitigation measures currently in use on national road schemes. This review was carried out taking cognisance of best international practices for noise assessment and methodologies used to mitigate road traffic noise. The primary focus of the study was to assess the actual noise impacts of national road scheme developments and to revise, where necessary, methodologies recommended in the current NRA guidance document describing the treatment of noise on national road schemes. This paper presents a summary of the study and identifies a number of key areas that should be considered prior to the development of future guidance documents. - Highlights: Black-Right-Pointing-Pointer Presents a post-EIS evaluation of noise assessments for national roads in Ireland. Black-Right-Pointing-Pointer The effectiveness of some noise mitigation measures is critically evaluated. Black-Right-Pointing-Pointer Issues related to the current EIS noise assessment methodologies are discussed. Black-Right-Pointing-Pointer Implications for alterations to the NRA noise guidelines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Crack Propagation Analysis Using Acoustic Emission Sensors for Structural Health Monitoring Systems

Aerospace systems are expected to remain in service well beyond their designed life. Consequently, maintenance is an important issue. A novel method of implementing artificial neural networks and acoustic emission sensors to form a structural health monitoring (SHM) system for aerospace inspection routines was the focus of this research. Simple structural elements, consisting of flat aluminum plates of AL 2024‐T3, were subjected to increasing static tensile loading. As the loading increased, designed cracks extended in length, releasing strain waves in the process. Strain wave signals, measured by acoustic emission sensors, were further analyzed in post‐processing by artificial neural networks (ANN). Several experiments were performed to determine the severity and location of the crack extensions in the structure. ANNs were trained on a portion of the data acquired by the sensors and the ANNs were then validated with the remaining data. The combination of a system of acoustic emission sensors, and an ANN could determine crack extension accurately. The difference between predicted and actual crack extensions was determined to be between 0.004 in. and 0.015 in. with 95% confidence. These ANNs, coupled with acoustic emission sensors, showed promise for the creation of an SHM system for aerospace systems.

42 ENGINEERING↗
DOE OSTI2022

Influence of weather on gobbling activity of male wild turkeys

Gobbling activity of Eastern wild turkeys (Meleagris gallopavo silvestris; hereafter, turkeys) has been widely studied, focusing on drivers of daily variation. Weather variables are widely believed to influence gobbling activity, but results across studies are contradictory and often equivocal, leading to uncertainty in the relative contribution of weather variables to daily fluctuations in gobbling activity. Previous works relied on road-based auditory surveys to collect gobbling data, which limits data consistency, duration, and quantity due to logistical difficulties associated with human observers and restricted sampling frames. Development of new methods using autonomous recording units (ARUs) allows researchers to collect continuous data in more locations for longer periods of time, providing the opportunity to delve into factors influencing daily gobbling activity. We used ARUs from 1 March to 31 May to detail gobbling activity across multiple study sites in the southeastern United States during 2014–2018. We used state-space modeling to investigate the effects of weather variables on daily gobbling activity. Our findings suggest rainfall, greater wind speeds, and greater temperatures negatively affected gobbling activity, whereas increasing barometric pressure positively affected gobbling activity. Therefore, when using daily gobbling activity to make inferences relative to gobbling chronology, reproductive phenology, and hunting season frameworks, stakeholders should recognize and consider the potential influences of extended periods of inclement weather.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Uncovering acoustic signatures of pore formation in laser powder bed fusion

Abstract We present a machine learning workflow to discover signatures in acoustic measurements that can be utilized to create a low-dimensional model to accurately predict the location of keyhole pores formed during additive manufacturing processes. Acoustic measurements were sampled at 100 kHz during single-layer laser powder bed fusion (LPBF) experiments, and spatio-temporal registration of pore locations was obtained from post-build radiography. Power spectral density (PSD) estimates of the acoustic data were then decomposed using non-negative matrix factorization with custom $$\varvec{k}$$ k -means clustering (NMF $$\varvec{k}$$ k ) to learn the underlying spectral patterns associated with pore formation. NMF $$\varvec{k}$$ k returned a library of basis signals and matching coefficients to blindly construct a feature space based on the PSD estimates in an optimized fashion. Moreover, the NMF $$\varvec{k}$$ k decomposition led to the development of computationally inexpensive machine learning models which are capable of quickly and accurately identifying pore formation with classification accuracy of supervised and unsupervised label learning greater than 95% and 90%, respectively. The intrinsic data compression of NMF k , the relatively light computational cost of the machine learning workflow, and the high classification accuracy makes the proposed workflow an attractive candidate for edge computing toward in-situ keyhole pore prediction in LPBF.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Laboratory Evaluation of the Thermal Breakout Method for Maximum Horizontal Stress Measurement

Measuring in situ stress is essential for many problems in geomechanics, and the maximum horizontal stress is the most difficult to constrain. We are developing an extension of the breakout method to measure maximum horizontal stress in regions where natural breakouts do not occur. In the novel thermal breakout method, additional compression which leads to breakout development is induced by heating the borehole wall. In the present study, we validated the method experimentally in a true-triaxial apparatus on samples with predrilled boreholes. Two rocks were selected for laboratory testing: high-porosity Berea sandstone and low-porosity Niagaran dolomite. Prior to main true-triaxial tests, we carried out standard testing to characterize the strength, elasticity and thermal properties. The true-triaxial experiments consisted of: (1) room-temperature tests where samples were first loaded mechanically until the breakout formed, and (2) elevated-temperature tests where samples were loaded mechanically within the elastic range with additional compression induced thermally. Breakout initiation was monitored by acoustic emission sensors mounted on the pistons that applied horizontal stresses. Furthermore, the magnitude of induced thermal stress was calculated from temperature measurements around the borehole wall. In both rock types, we created thermally induced breakouts and examined analytical expressions to constrain maximum horizontal stress based on strength, elastic and thermal properties of the rocks.

58 GEOSCIENCES↗
DOE OSTI2022

Classification of animal sounds in a hyperdiverse rainforest using convolutional neural networks with data augmentation

To protect tropical forest biodiversity, we need to be able to detect it reliably, cheaply, and at scale. Automated detection of sound producing animals from passively recorded soundscapes via machine-learning approaches is a promising technique towards this goal, but it is constrained by the necessity of large training data sets. Using soundscapes from a tropical forest in Borneo and a Convolutional Neural Network model (CNN), we investigate i) the minimum viable training data set size for accurate prediction of call types (‘sonotypes’), and ii) the extent to which data augmentation and transfer learning can overcome the issue of small and imbalanced training data sets. We found that even relatively high sample sizes (>80 per sonotype) lead to mediocre accuracy, which however improved significantly with data augmentation and transfer learning, including at extremely small sample sizes (3 per sonotype), regardless of taxonomic group or call characteristics. Neither transfer learning nor data augmentation alone achieved high accuracy. Our results suggest that transfer learning and data augmentation could make the use of CNNs to classify species’ vocalizations feasible even for small soundscape-based projects with many rare species. Retraining our open-source model requires only basic programming skills which makes it possible for individual conservation initiatives to match their local context, in order to enable more evidence-informed management of biodiversity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Evaluating musical instruments

Scientific measurements of sound generation and radiation by musical instruments are surprisingly hard to correlate with the subtle and complex judgments of instrumental quality made by expert musicians.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Experimental validation of a high voltage pulse measurement method.

This report describes X-cut lithium niobate s (LiNbO3) utilization for voltage sensing by monitoring the acoustic wave propagation changes through LiNbO3 resulting from applied voltage. Direct current (DC), alternating current (AC) and pulsed voltage signals were applied to the crystal. Voltage induced shift in acoustic wave propagation time scaled quadratically for DC and AC voltages and linearly for pulsed voltages. The measured values ranged from 10 - 273 ps and 189 ps 2 ns for DC and non-DC voltages, respectively. Data suggests LiNbO3 has a frequency sensitive response to voltage. If voltage source error is eliminated through physical modeling from the uncertainty budget, the sensor s U95 estimated combined uncertainty could decrease to ~0.025% for DC, AC, and pulsed voltage measurements.

Cular, Stefan↗
DOE OSTI2015

Advanced Offshore Wind Energy: Atlantic Consortium

This project developed relationships among the lead institution, U of Delaware, wind industry participants from 11 companies, and two other universities in the region. The participating regional universities were University of Maryland and Old Dominion University. Research was carried out in six major areas: Analysis and documentation of extreme oceanic wind events & their impact on design parameters, calibration of corrosivity estimates measured on a coastal turbine, measurment and modeling of tower structures, measurement and modeling of the tribology of major drive components, and gearbox conditioning monitoring using acoustic sensors. The project also had several educational goals, including establishing a course in wind energy and training graduate students. Going beyond these goals, three new courses were developed, a graduate certificate program in wind power was developed and approved, and an exchange program in wind energy was established with Danish Technical University. Related to the installation of a Gamesa G90 turbine on campus and a Gamesa-UD research program established in part due to this award, several additional research projects have been carried out based on mutual industry-university interests, and funded by turbine revenues. This award and the Gamesa partnership have jointly led to seven graduate students receiving full safety and climb training, to become “research climbers” as part of their wind power training, and contributing to on-turbine research. As a result of the educational program, already six graduate students have taken jobs in the US wind industry.

17 WIND ENERGY↗
DOE OSTI2021

Acoustic and Genetic Approaches for Informing Population Status and Trends of Migratory Tree Bats

Through the systematic collection of acoustic and genetic data over time, a weight of evidence may be built that will support an improved understanding around population stability for migratory tree-roosting bat species. This information can be leveraged to infer the influence stressors have on population stability, and subsequently determine the level of response necessary to sustain healthy populations. Here, we synthesize the existing information related to bat population status and trends, uncertainty regarding existing estimates, current and novel methods for assessing population-level data, and recommendations for near-term and long-term studies to reduce uncertainty surrounding population data. Although this report focuses on wind energy development and bats, the methods used are broadly applicable and are being implemented by other industries, academia, government agencies, and nongovernmental organizations. Through efforts outside of the wind energy industry, it is likely we will gain a better understanding of bat populations, but the pace of data collection and analysis will be expedited by further participation by the wind energy industry. In return, the wind energy industry will benefit by contributing to these efforts either by 1) discovering that the population status of the species of interest is stable or growing, which may prevent the need for listing one or more species; or 2) recognizing the population status of certain species is in decline and implementing relatively moderate measures to reduce wind turbine-related mortality in the near term to stave off more stringent measures, which may be necessary if action is delayed.

17 WIND ENERGY↗
NASA NTRS1973

Detection of fatigue cracks by nondestructive testing methods

The effectiveness was assessed of various NDT methods to detect small tight cracks by randomly introducing fatigue cracks into aluminum sheets. The study included optimizing NDT methods calibrating NDT equipment with fatigue cracked standards, and evaluating a number of cracked specimens by the optimized NDT methods. The evaluations were conducted by highly trained personnel, provided with detailed procedures, in order to minimize the effects of human variability. These personnel performed the NDT on the test specimens without knowledge of the flaw locations and reported on the flaws detected. The performance of these tests was measured by comparing the flaws detected against the flaws present. The principal NDT methods utilized were radiographic, ultrasonic, penetrant, and eddy current. Holographic interferometry, acoustic emission monitoring, and replication methods were also applied on a reduced number of specimens. Generally, the best performance was shown by eddy current, ultrasonic, penetrant and holographic tests. Etching provided no measurable improvement, while proof loading improved flaw detectability. Data are shown that quantify the performances of the NDT methods applied.

Anderson, R. T.↗
NASA NTRS1978

Reclaiming hybrid integrated circuits

Reclamation method consists of opening very small hole in package and shaking out trapped particles. Procedure is performed in dry box through which an inert gas is flowing to insure no room air enters package. Acoustic transducer monitors sound of vibrating particles. Amplifier produces audio and oscilloscope output. Hole is sealed with heated solder form.

Ebel, G.↗
NASA NTRS1977

Acoustic emission during unloading of elastically stressed magnesium alloy

A magnesium alloy was quasi-statically cycled elastically between zero load and tension. Both loading and unloading stress delays were found, and the unloading stress delay was further studied. An analytical expression was written for the unloading stress delay which is an elastic constitutive parameter. The potential use of these results for the acoustic emission monitoring of elastic stress states is discussed.

Lee, S. S.↗
NASA NTRS1982

Acoustic Emissions Could Indicate Weld Quality

Preliminary tests show quality of welds can be assessed by acoustic-emission monitor mounted on welder. Nondestructive measurement technique allows operator to determine uniformity and integrity of weld as being made, evaluate equipment performance and condition, and initiate corrective action if quality is not satisfactory.

Gustafson, P. E.↗
NASA NTRS1981

Analysis of the inversion monitoring capabilities of a monostatic acoustic radar in complex terrain

A qualitative interpretation of the records from a monostatic acoustic radar is presented. This is achieved with the aid of airplane, helicopter, and rawinsonde temperature soundings. The diurnal structure of a mountain valley circulation pattern is studied with the use of two acoustic radars, one located in the valley and one on the downwind ridge. The monostatic acoustic radar was found to be sufficiently accurate in locating the heights of the inversions and the mixed layer depth to warrant use by industry even in complex terrain.

Koepf, D.↗