Flight determination of the aerodynamic stability and control characteristics of the NASA SGS 1-36 sailplane in the conventional and deep stall angles-of-attack of between -5 and 75 degrees

The flight test procedure and the preliminary analysis of the results obtained from twenty manned flights of the SGS 1-36 in the high angles of attack Deep Stall region are discussed. A comparison of the flight determined stability and control derivatives, those of the wind tunnel, and the estimated aerodynamic data is also presented. Furthermore, deep stall dynamics response of the SGS 1-36 is discussed briefly to explain some of the unexpected flight observations

The Effect of Energy Transportation of High-Energy Electrons on the Electromagnetic Instability

The energy transportation of High-energy electrons to the compressed fuel and study of affected factors on it are the most important issues in fast ignition method. In this research, regarding the role of Weibel instability in process modulation and possible impacts of electron and plasma beam velocity to reach higher energy yields, the effect of temporal variation of particle distribution in the presence of laser electric fields on growth andcondition of Weibel instability in beam-plasma medium were investigated in the form of a classic system without any Coulombic collision between the particles and magnetic fields. The results show that the time-dependent drift velocity leads to a decrease the growth rate of the Weibel when energy transportation of energetic particles to the fusion plasma systems increases

On the utility of occupants’ behavioural diversity information for building performance simulation: An exploratory case study

The present study aims at investigating the potential advantages of integrating inter-occupant diversity information into occupant behaviour models used in building performance simulation. To this end, the authors model the operation of windows by occupants in a monitored open-plan office at aggregate and individual levels. The models use indoor and outdoor temperature as well as the interaction of these variables to estimate the probability of opening and closing windows in the building located in Vienna, Austria. Subsequently, a number of existing and novel metrics serve to compare the predictive performance of the aggregate and individual models. In addition, a calibrated energy model of the office area incorporates the window operation models to evaluate their potential contribution to the reliability of building performance assessments. The results of this exploratory case study suggest that individual window operation models outperform the aggregate model in capturing the peak and variations of window operation across occupants. This resulted in a more reliable thermal comfort assessment in the free-running season. The individual models, however, overestimated peak heating demand, as compared with the benchmark value resulting from the actual window operations in a single year

Analysis of agile canine gait characteristics using accelerometry

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. The high rate of severe injuries associated with racing greyhounds poses a significant problem for both animal welfare and the racing industry. Using accelerometry to develop a better understanding of the complex gait of these agile canines may help to eliminate injury contributing factors. This study used a single Inertial Measurement Unit (IMU) equipped with a tri-axial accelerometer to characterise the galloping of thirty-one greyhounds on five different race tracks. The dorsal-ventral and anterior-posterior accelerations were analysed in both the time and frequency domains. The fast Fourier transform (FFT) and Morlet wavelet transform were applied to signals. The time-domain signals were synced with the corresponding high frame rate videos of the race. It is observed that the acceleration peaks in the dorsal-ventral accelerations correspond to the hind-leg strikes which were noted to be fifteen times the greyhound’s weight. The FFT analysis showed that the stride frequencies in all tracks were around 3.5 Hz. The Morlet wavelet analysis also showed a reduction in both the frequency and magnitude of signals, which suggests a speed reduction throughout the race. Also, by detecting abrupt changes along the track, the wavelet analysis highlighted potentially hazardous locations on the track. In conclusion, the methods applied in this research contribute to animal safety and welfare by eliminating the factors leading to injuries through optimising the track design and surface type

Morphological abnormality among regenerated shoots of banana and plantain (Musa spp.) after in vitro multiplication with TDZ and BAP from excised shoottips

Five cultivars of Musa spp (banana and plantain); ‘Berangan Intan’, ‘Berangan’ (AAA), ‘Rastali’, ‘Nangka’ (AAB) and ‘Baka Baling’ (ABB) were chosen to compare the effect of benzylaminopurine (BAP) and thidiazuron (TDZ) on multiplication efficiency in relation with frequency of abnormal shoot regeneration. Shoot tips of Musa spp. were cultured on MS medium supplemented with various concentrations (0.0, 11.1, 22.2, 33.3 and 44.4 ìM) of BAP and (0.0, 0.5, 2, 5 and 7.5 ìM) of TDZ. Increasing BAP above 22.2 ìM and 33.3 ìM increased the number of shoots in ‘Berangan Intan’,‘Berangan’, ‘Rastali’, ‘Nangka’ and ‘Baka Baling’ respectively, but above 33.3 ìM significantly caused higher gross of abnormal shoot regeneration. TDZ in the media up to 2 ìM for ‘Baka Baling’, ‘Nangka’ and ‘Rastali’ and 5 ìM for ‘Berangan Intan’ and ‘Berangan’ increased the number of shoots per explant,however TDZ at 5 ìM resulted in high number of abnormal shoots. In conclusion BAP at 22.2 ìM and TDZ at 2 ìM were assumed to be the most suitable for commercial micropropagation system with low frequency of abnormal shoot production for both banana and plantain

Effects of fennel (Foeniculum vulgare) essential oil of diet on some biochemical parameters and salinity stress resistance of kutum (Rutilus kutum) fry

This study was carried out to investigate the effects of different levels of fennel essential oil (Foeniculum vulgare) on some biochemical parameters and salinity stress resistance of Caspian Kutum (Rutilus kutum) fry. For this purpose, Kutum fry with an average initial weight 0.6±0.002 gr were divided randomly in 5 treatments including 0 (control), 100, 200,400 and 600 mg fennel essential oil/kg diet and fed 3 times a day at a ratio of 7-12% body weight for 60 days. At the end of the experiment, biochemical parameters and salinity stress resistance were assessed. Results of serum biochemical analyze showed that the highest level of total protein and globulin was observed in 600 mg fennel essential oil/kg diet. The highest level of albumin and cholesterol was observed in 100 and 400 mg fennel essential oil/kg diet and the highest level of triglyceride, glucose and cortisol was observed in control (p<0.05). Results of salinity stress (6, 13 and 20 g/l) showed that 100 and 400 mg fennel essential oil/kg diet treatments showed the lowest response to stress and there were the lowest changes in cortisol and glucose levels before and after stress compare to control. Highest survival was observed in 100 and 400 mg fennel essential oil/kg diet. In conclusion results suggested that Fennel essential oil can improve immune system of fries by promoting biochemical parameters (total protein, albumin, globulin, triglyceride, glucose and cortisol). Also plays important role in increasing stress resistance of Kutum fry and the best operation is related to 100 mg fennel essential oil/kg diet

Monitored data on occupants’ presence and actions in an office building

Within a study, an open plan area and one closed office in a university building with a floor area of around 200 m2 were monitored. The present data set covers a period of one year (from 2013-01-01 to 2013-12-31). The collected data pertains to indoor environmental conditions (temperature, humidity) as well as plug loads and external factors (temperature, humidity, wind speed, and global irradiance) along with occupants’ presence and operation of windows and lights. The monitored data can be used for multiple purposes, including the development and validation of occupancy-related models

Investigation of inverse design of multilayer thin-films with conditional invertible Neural Networks

The task of designing optical multilayer thin-films regarding a given target is currently solved using gradient-based optimization in conjunction with methods that can introduce additional thin-film layers. Recently, Deep Learning and Reinforcement Learning have been been introduced to the task of designing thin-films with great success, however a trained network is usually only able to become proficient for a single target and must be retrained if the optical targets are varied. In this work, we apply conditional Invertible Neural Networks (cINN) to inversely designing multilayer thin-films given an optical target. Since the cINN learns the energy landscape of all thin-film configurations within the training dataset, we show that cINNs can generate a stochastic ensemble of proposals for thin-film configurations that that are reasonably close to the desired target depending only on random variables. By refining the proposed configurations further by a local optimization, we show that the generated thin-films reach the target with significantly greater precision than comparable state-of-the art approaches. Furthermore, we tested the generative capabilities on samples which are outside the training data distribution and found that the cINN was able to predict thin-films for out-of-distribution targets, too. The results suggest that in order to improve the generative design of thin-films, it is instructive to use established and new machine learning methods in conjunction in order to obtain the most favorable results

Multi-stage calibration of the simulation model of a school building through short-term monitoring

The increasing attention on the improvement of new and existing buildings' performance is emphasizing the importance of the reliability of the simulation models in predicting the complexity of the building behaviour and, consequently, in some advanced applications of building simulation, such as the optimization of the choice of different Energy Efficiency Measures (EEMs) or the adoption of model predictive control strategies. The reliability of the energy model does not depend only on the quality and details of the model itself, but also on the uncertainty related to many input values, such as the physical properties of materials and components, the information on the building management and occupation, and the boundary conditions considered for the simulation. Especially for the existing buildings, this kind of data is often missing or characterized by high uncertainty, and only very simplified behavioural models of occupancy are available. This could compromise the optimization process and undermine the potential of building simulation. In this context, the calibration of the simulation model by means of on-site monitoring is of crucial importance to increase the reliability of the predictions, and to take better decisions, even though this process can be time consuming. This work presents a multi-stage methodology to calibrate the building energy simulation by means of low-cost monitoring and short-term measurements. This approach is applied to a Primary School in the North-East of Italy, which has been monitored from December 2012 to April 2014. Four monitoring periods have been selected to calibrate different sets of variables at a time, while the validation has been carried out on two different periods. The results show that even if less than 8 weeks have been considered in the proposed calibration approach, the maximum error in the estimation of the temperature is less than ±0.5 in 77.3% of the timesteps in the validation period