Early Forest Fire Detection Using Radio-Acoustic Sounding System

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires

Sonic Booms in Atmospheric Turbulence (SonicBAT): The Influence of Turbulence on Shaped Sonic Booms

The objectives of the Sonic Booms in Atmospheric Turbulence (SonicBAT) Program were to develop and validate, via research flight experiments under a range of realistic atmospheric conditions, one numeric turbulence model research code and one classic turbulence model research code using traditional N-wave booms in the presence of atmospheric turbulence, and to apply these models to assess the effects of turbulence on the levels of shaped sonic booms predicted from low boom aircraft designs. The SonicBAT program has successfully investigated sonic boom turbulence effects through the execution of flight experiments at two NASA centers, Armstrong Flight Research Center (AFRC) and Kennedy Space Center (KSC), collecting a comprehensive set of acoustic and atmospheric turbulence data that were used to validate the numeric and classic turbulence models developed. The validated codes were incorporated into the PCBoom sonic boom prediction software and used to estimate the effect of turbulence on the levels of shaped sonic booms associated with several low boom aircraft designs. The SonicBAT program was a four year effort that consisted of turbulence model development and refinement throughout the entire period as well as extensive flight test planning that culminated with the two research flight tests being conducted in the second and third years of the program. The SonicBAT team, led by Wyle, includes partners from the Pennsylvania State University, Lockheed Martin, Gulfstream Aerospace, Boeing, Eagle Aeronautics, Technical & Business Systems, and the Laboratory of Fluid Mechanics and Acoustics (France). A number of collaborators, including the Japan Aerospace Exploration Agency, also participated by supporting the experiments with human and equipment resources at their own expense. Three NASA centers, AFRC, Langley Research Center (LaRC), and KSC were essential to the planning and conduct of the experiments. The experiments involved precision flight of either an F-18A or F-18B executing steady, level passes at supersonic airspeeds in a turbulent atmosphere to create sonic boom signatures that had been distorted by turbulence. The flights spanned a range of atmospheric turbulence conditions at NASA Armstrong and Kennedy in order to provide a variety of conditions for code validations. The SonicBAT experiments at both sites were designed to capture simultaneous F-18A or F-18B onboard flight instrumentation data, high fidelity ground based and airborne acoustic data, surface and upper air meteorological data, and additional meteorological data from ultrasonic anemometers and SODARs to determine the local atmospheric turbulence and boundary layer height

Turbulence-Turbine Interaction: The Basis for the Development of the TurbSim Stochastic Simulator

A combination of taller wind turbines with more flexible rotors and towers operating in turbulent conditions that are not well understood is contributing to much higher than anticipated maintenance and repairs costs and is associated with lower energy production. This report documents evidence of this and offers the turbine designers an expanded tool that resolves many of these shortcomings

Innovative Strategies for Observations in the Arctic Atmospheric Boundary Layer

In this thesis, consisting of five scientific papers, I investigate the potential of unmanned aircraft systems (UAS) in stable boundary layer (SBL) research, by developing and applying a new innovative observation strategy. In this strategy we supplement ground-based micrometeorological observations from masts and remote-sensing systems with a number of different UAS. To achieve good agreement between the different systems employed in this approach, I further investigate the quality and intercomparability of UAS-based observations of atmospheric temperature, humidity, pressure and wind, and develop and apply common, best-practice data processing methods. In Paper I we give a brief introduction to the ISOBAR project and provide an overview over the first SBL campaign at Hailuoto and the prevailing synoptic, sea-ice and micrometeorological conditions. We demonstrate the quality of our measurement approach by combining UAS profile data with observations from the wind and temperature sensing systems. Repeated UAS temperature profiles give detailed insight into the temporal evolution of the SBL, which we find was often subject to rapid temperature changes affecting the entire depth of the SBL. We further highlight the potential of the sampled data by detailed investigations of a case study, featuring rapid shifts in turbulent regimes and strong elevated thermal instabilities, which were likely to result from the instability of an elevated internal gravity wave. In Paper II we assess the quality and intercomparability of UAS-based atmospheric observations from the most extensive intercomparison experiment to date. We evaluate the precision and bias of temperature, humidity, pressure, wind speed and direction observations from 38 individual UAS with 23 unique sensor configurations based on observations next to a 18-m mast equipped with reference instruments. In addition, we investigate the influence of sensor response on the quality of temperature and humidity profiles. By grouping the different sensor–platform combinations with respect to the type of aircraft, sensor type and sensor integration (i.e., measures for aspiration and radiation shielding), we attempt to draw general conclusions from the intercomparison results. Overall, we find most observation systems in good agreement with the reference observations, however, some systems showed fairly large biases. In general, hovering multicopters showed less variability than fixed-wing systems and we attribute this finding to the difference in sampling strategies. The most consistent observations of the mean wind were achieved by multicopter-mounted sonic anemometers. Sensor response errors were smaller for fine-bed thermistors compared to temperature sensors of integrated-circuit type, and sensor aspiration proofed to be substantially relevant. We conclude, that sensor integration considerations, like radiation shielding and aspiration, are likely to be as important as the choice of the sensor type, and give a couple of recommendations for future perspectives on UAS-based atmospheric measurements. Paper III presents the ISOBAR project to a broader scientific audience, including a description of the two measurement campaigns, ISOBAR17 and ISOBAR18 and the contrasting meteorological and sea ice conditions. We further provide an overview on the micrometeorological conditions during the 13 intensive observational periods (IOPs), which resulted in detailed data sets on the SBL in unprecedented spatiotemporal resolution. Numerous cases with very-stable stratification under clear-sky and weak-wind conditions were observed, featuring a variety of different SBL processes. These processes resulted in rapid changes in the SBL’s vertical structure. Based on selected in-depth case studies, we investigate the interactions of turbulence in the very stable boundary layer (VSBL) with different processes, i.e., a shear instability, associated with a low-level jet; a rapid and strong cooling event, observed a couple of meters above the ground; and a wave-breaking event, caused by the enhancement of wind shear. In a first qualitative model validation experiment we use data from one IOP to assess the performance of three different types of numerical models. Only the turbulence resolving large-eddy simulation model is found capable of reproducing a VSBL structure similar to the one observed during the IOP. The other models, i.e., an operational weather prediction and a single-column model, substantially overestimated the depth of the SBL. Paper IV introduces a new fixed-wing UAS for turbulence observations and first results from validation experiments carried out during ISOBAR18. Airborne observations of mechanical turbulence from straight horizontal flight paths are compared to corresponding eddy-covariance measurements mounted on a 10-m mast during weakly stable conditions with moderate wind speeds. Different average and spectral turbulence quantities, as well as mean wind speed and direction were computed for both systems and compared to each other. The UAS observations of mean wind and turbulence are in good agreement with the reference observations and the turbulence spectra agree qualitatively in the onset of the inertial subrange and the turbulence production range. Minor differences are likely to be caused by a slightly elevated UAS flight level and additional small altitude variations in the presence of relatively strong vertical gradients. In a second comparison, vertical profiles of mean wind and turbulence variables, determined from straight horizontal UAS flights at several different levels are compared qualitatively to profile observations from the 10-m mast and a phased-array sodar system providing 10-min averaged wind and vertical velocity variance profiles above 35 m. Qualitatively, the results agree well for the first two out of three profiles. During the third profile, the UAS data indicate the existence of a low-level jet but not an upside-down boundary layer structure, which would be expected due to the elevated source of turbulence. This observation is, however, not supported by the other measurement systems. Instead, the sodar data indicate a strong decrease in wind speed during the time of this profile. The fact that the lower part of the UAS profile was sampled before the start of the strongest transition, resulted in a seemingly wrong shape of the vertical profiles. This finding highlights the relevance of non-stationarity and the importance of additional reference systems for the correct interpretation of UAS sampled turbulence profiles. Paper V explores the potential of a new method to estimate profiles of turbulence variables in the SBL. In this method we apply a gradient-based scaling scheme for SBL turbulence to multicopter profiles of temperature and wind, sampled during ISOBAR18. We first validate this method by scaling turbulence observations from three levels on a 10-m mast with the corresponding scaling parameters, and comparing the resulting non- dimensional parameters to the semi-empirical stability functions proposed for this scheme. The scaled data from the three levels largely collapse to the predicted curves, however, minor differences between the three levels are evident. We attribute this discrepancy to the non-ideal observation heights for the determination of vertical gradients at the upper turbulence observation level. After the successful validation we apply this method to UAS profiles, by computing profiles of the gradient Richardson number to which we then apply the stability functions to derive turbulence variables. We demonstrate this approach based on three case studies covering a broad range of SBL conditions and boundary layer heights. Since the application of this scaling scheme is only valid within the SBL, we estimate the boundary layer height from the sodar and two different methods based on UAS data. Comparisons at the lowest levels against turbulence variables from the 10-m mast and at higher levels against a Doppler wind lidar, which also provides estimates of some turbulence variables, indicate broad agreement and physical meaningful results of this method. Supplementing the findings from the five scientific papers, this thesis also provides the detailed description on the methodology and data processing procedures, I applied for the synthesis of observations from UAS, micrometeorological masts and boundary layer remote-sensing systems. Furthermore, I present results on the validation of the different wind observation methods, using lidar wind observations as the common reference. Finally, I provide an outlook on future perspectives of SBL and UAS-based boundary-layer research, and how further developments in SBL observation strategies may benefit from recent and future developments.Doktorgradsavhandlin

Dynamics of Bora wind over the Adriatic sea: atmospheric water balance and role of air-sea fluxes and orography

The Bora wind is a mesoscale phenomenon which typically affects the Adriatic Sea basin for several days each year, especially during winter. The Bora wind has been studied for its intense outbreak across the Dinaric Alps. The properties of the Bora wind are widely discussed in the literature and scientific papers usually focus on the eastern Adriatic coast where strong turbulence and severe gust intensity are more pronounced. However, the impact of the Bora wind can be significant also over Italy, not only in terms of wind speed instensity. Depending on the synoptic pressure pattern (cyclonic or anticyclonic Bora) and on the season, heavy snowfall, severe storms, storm surges and floods can occur along the Adriatic coast and on the windward flanks of the Apennines. In the present work five Bora cases that occurred in recent years have been selected and their evolution has been simulated with the BOLAM-MOLOCH model set, developed at ISAC-CNR in Bologna. Each case study has been addressed by a control run and by several sensitivity tests, performed with the purpose of better understanding the role played by air-sea latent and sensible heat fluxes. The tests show that the removal of the fluxes induces modifications in the wind approching the coast and a decrease of the total precipitation amount predicted over Italy. In order to assess the role of heat fluxes, further analysis has been carried out: column integrated water vapour fluxes have been computed along the Italian coastline and an atmospheric water balance has been evaluated inside a box volume over the Adriatic Sea. The balance computation shows that, although latent heat flux produces a significant impact on the precipitation field, its contribution to the balance is relatively minor. The most significant and lasting case study, that of February 2012, has been studied in more detail in order to explain the impressive drop in the total precipitation amount simulated in the sensitivity tests with removed heat fluxes with respect to the CNTRL run. In these experiments relative humidity and potential temperature distribution over different cross-sections have been examined. With respect to the CNTRL run a drier and more stable boundary layer, characterised by a more pronounced wind shear at the lower levels, has been observed to establish above the Adriatic Sea. Finally, in order to demonstrate that also the interaction of the Bora flow with the Apennines plays a crucial role, sensitivity tests varying the orography height have been considered. The results of such sensitivity tests indicate that the propagation of the Bora wind over the Adriatic Sea, and in turn its meteorological impact over Italy, is influenced by both the large air-sea heat fluxes and the interaction with the Apennines that decelerate the upstream flow

Wafer defect recognition method based on multi-scale feature fusion

Wafer defect recognition is an important process of chip manufacturing. As different process flows can lead to different defect types, the correct identification of defect patterns is important for recognizing manufacturing problems and fixing them in good time. To achieve high precision identification of wafer defects and improve the quality and production yield of wafers, this paper proposes a Multi-Feature Fusion Perceptual Network (MFFP-Net) inspired by human visual perception mechanisms. The MFFP-Net can process information at various scales and then aggregate it so that the next stage can abstract features from the different scales simultaneously. The proposed feature fusion module can obtain higher fine-grained and richer features to capture key texture details and avoid important information loss. The final experiments show that MFFP-Net achieves good generalized ability and state-of-the-art results on real-world dataset WM-811K, with an accuracy of 96.71%, this provides an effective way for the chip manufacturing industry to improve the yield rate