建议气瓶充装前增加气瓶音响检查项目

高压无缝钢瓶的充装前检查 ,在现有的标准或规程中是没有音响检查这一项内容的 ,只有在气瓶定期检验时 ,根据国家标准GB 130 0 4— 1999《钢质无缝气瓶定期检验与评定》中有音响检查的要求 ,但气瓶定期检验周期为二至五年。有关资料表明 ,当氧气瓶中进入海水或其他腐蚀物 ,则该瓶使用半年至一年后 ,瓶体被腐蚀处的剩余壁厚不到 2mm ,这样的气瓶如混入充装站 ,在充装过程中就很有可能发生事故。所以 ,只在气瓶定期检验中才进行一次音响检查 ,已经不能满足气瓶充装安全生产的需要。气瓶充装前的音响检查 ,可引用GB 130 0 4—1999《钢质无缝…     

Depollution of atmospheric emissions of wood pyrolysis furnaces

The wood carbonization in Tunisia consists essentially of traditional activity using charcoaling stacks and pits characterized by high atmospheric pollution and poor energy conversion. Indeed, 70% of the initial mass of anhydrous wood are found in the vapor as aerosols, polluting and toxic gases and complex condensable organic compounds that can cause a substantial pollution of air, ground and water. Several processes of treatment and energy valorization of such effluents were proposed, but the incineration remains at present the most promising technique of depollution. The results show that the incineration, at about 1000°C, of wood carbonization smokes allows the destruction of 99% of the mass of pollutants except CO₂ and the reduction of polluting gas emission. The possible valorization of the smoke’s energy in the exit of the incinerator enhances the thermal efficiency of the process.     

Forecasting based on sectoral energy consumption of GHGs in Turkey and mitigation policies

Recently, global warming and its effects have become one of the most important themes in the world. Under the Kyoto Protocol, the EU has agreed to an 8% reduction in its greenhouse gas (GHG) emissions by 2008–2012. The GHG emissions (total GHG, CO₂, CO, SO₂, NO₂, E (emissions of non-methane volatile organic compounds)) covered by the Protocol are weighted by their global warming potentials (GWPs) and aggregated to give total emissions in CO₂ equivalents. The main subject in this study is to obtain equations by the artificial neural network (ANN) approach to predict the GHGs of Turkey using sectoral energy consumption. The equations obtained are used to determine the future level of the GHG and to take measures to control the share of sectors in total emission. According to ANN results, the maximum mean absolute percentage error (MAPE) was found as 0.147151, 0.066716, 0.181901, 0.105146, 0.124684, and 0.158157 for GHG, SO₂, NO₂, CO, E, and CO₂, respectively, for the training data with Levenberg–Marquardt (LM) algorithm by 8 neurons. R² values are obtained very close to 1. Also, this study proposes mitigation policies for GHGs.     

Electronic Emissions Security: Danger in the Air

Most organizations have measures to protect their network infrastructure from intruders. With the growth AND AVAILABILITY of wireless, some intruders now are aiming their attacks there. The potential for damage from these types of attacks is significant due to their nature. However, there is another type of wireless attack on organizational resources that also poses a significant vulnerability. That is electromagnetic radiation, also called radio frequency emissions (RFE), from unprotected systems and networks.     

The impact of CHP generation on CO2 emissions

The combined generation of heat and power (cogeneration) is praised by many as a technique for reducing the emissions of CO₂ in industrialized nations. This is generally true but not always. In this article we discuss the impact of some major variables on the CO₂ emission reduction capacity of cogeneration. Two sets of variables are predominant: the characteristics of the CHP process and the composition of the electricity generation sector. We highlight the interaction between the two sets of variables with the help of diagrams.     

Analysis of a conjugated infinite element method for acoustic scattering

This work is devoted to a study of a conjugated infinite element method for Helmholtz problems in exterior domains. A formulation of this method with Lagrange multipliers defined on (semi-)infinite space is presented and analyzed in a domain decomposition context. The implementation aspects of this method in a parallel industrial acoustic software (SYSNOISE) are described in details. Numerical results show the computational efficiency of this method on acoustic scattering problems.     

An evaluation of possible EU air transport emissions trading scheme allocation methods

The European Commission has been requested by member states to study the incorporation of air transport into their existing emissions trading scheme (ETS). Only CO₂ is to be included, at least initially.     

Tributary use and large-scale movements of grass carp in Lake Erie

Infrequent captures of invasive, non-native grass carp (Ctenopharyngodon idella) have occurred in Lake Erie over the last 30+ years, with recent evidence suggesting wild reproduction in the lake’s western basin (WB) is occurring. Information on grass carp movements in the Laurentian Great Lakes is lacking, but an improved understanding of large-scale movements and potential areas of aggregation will help inform control strategies and risk assessment if grass carp spread to other parts of Lake Erie and other Great Lakes. Twenty-three grass carp captured in Lake Erie’s WB were implanted with acoustic transmitters and released. Movements were monitored with acoustic receivers deployed throughout Lake Erie and elsewhere in the Great Lakes. Grass carp dispersed up to 236 km, with approximately 25% of fish dispersing greater than 100 km from their release location. Mean daily movements ranged from <0.01 to 2.49 km/day, with the highest daily averages occurring in the spring and summer. The Sandusky, Detroit, and Maumee Rivers, and Plum Creek were the most heavily used WB tributaries. Seventeen percent of grass carp moved into Lake Erie’s central or eastern basins, although all fish eventually returned to the WB. One fish emigrated from Lake Erie through the Huron-Erie Corridor and into Lake Huron. Based on our results, past assessments may have underestimated the potential for grass carp to spread in the Great Lakes. We recommend focusing grass carp control efforts on Sandusky River and Plum Creek given their high use by tagged fish, and secondarily on Maumee and Detroit Rivers.     

Evidence of successful river spawning by lake trout (Salvelinus namaycush) in the Lower Niagara River,Lake Ontario

Restoration of a wild-produced lake trout Salvelinus namaycush population in Lake Ontario has not been successful despite the adult population often meeting or exceeding restoration targets. Lack of high-quality spawning habitat in Lake Ontario is suggested as one impediment to recruitment of wild lake trout, although the quantity and location of spawning habitat is poorly understood. If high-quality spawning habitat is limited in Lake Ontario, lake trout may be using uncommon spawning locations such as rivers. Anecdotal angler accounts point to the Niagara River as a lake trout spawning location. To better understand the potential of the Niagara River as a spawning location, egg and juvenile fish collections were conducted 12–14 river kilometers from the mouth of the Niagara River from 2010 to 2012; and mature female lake trout with surgically implanted acoustic tags were monitored from 2015 to 2019. Genetic analyses confirmed 60% of collected eggs and 93% of collected post-hatch juvenile fish in the Niagara River were lake trout. Tagged female lake trout returned to the Niagara River over consecutive years during the spawning season. The short duration of lake trout presence in the river (mean = 56 days/year) suggests female lake trout use the Niagara River primarily for spawning. Diversity in spawning locations may provide lake trout population’s resilience against environmental variability through a portfolio effect. Improved identification of riverine spawning locations, including their overall contribution to wild recruitment, may be a useful tool for managers to restore a wild-produced population of lake trout in Lake Ontario.     

LearningADD: Machine learning based acoustic defect detection in factory automation

Defect inspection of glass bottles in the beverage industrial is of significance to prevent unexpected losses caused by the damage of bottles during manufacturing and transporting. The commonly used manual methods suffer from inefficiency, excessive space consumption, and beverage wastes after filling. To replace the manual operations in the pre-filling detection with improved efficiency and reduced costs, this paper proposes a machine learning based Acoustic Defect Detection (LearningADD) system. Moreover, to realize scalable deployment on edge and cloud computing platforms, deployment strategies especially partitioning and allocation of functionalities need to be compared and optimized under realistic constraints such as latency, complexity, and capacity of the platforms. In particular, to distinguish the defects in glass bottles efficiently, the improved Hilbert-Huang transform (HHT) is employed to extend the extracted feature sets, and then Shuffled Frog Leaping Algorithm (SFLA) based feature selection is applied to optimize the feature sets. Five deployment strategies are quantitatively compared to optimize real-time performances based on the constraints measured from a real edge and cloud environment. The LearningADD algorithms are validated by the datasets from a real-life beverage factory, and the F-measure of the system reaches 98.48 %. The proposed deployment strategies are verified by experiments on private cloud platforms, which shows that the Distributed Heavy Edge deployment outperforms other strategies, benefited from the parallel computing and edge computing, where the Defect Detection Time for one bottle is less than 2.061 s in 99 % probability.