Suchergebnisse

Hybrid titanium composite laminates (HTCLs) are high-performance light-weight fiber metal laminates (FMLs) that are being increasingly used in various industries such as aeronautical, military, and marine thanks to their optimized fracture toughness, impact resistance, and thermal performance. In the current study, the low-velocity impact (LVI) characteristics of a new generation of thermoplastic (TP) HTCLs at various energy levels are investigated. To do so, Ti-6Al-4 V sheets, carbon fabrics, and ultra-high molecular weight polyethylene (UHMWPE) fabrics are used to fabricate multiple laminates with different fiber types, metal volume fractions, and lamination layups. A low-cost resin infusion process is employed for manufacturing the laminates at room temperature by using a novel liquid thermoplastic methyl methacrylate resin, Elium® 188. Before fabrication, a multi-step surface treatment method is applied on Ti alloy sheets to enhance the interfacial properties between the composite layer and the metal alloy sheet. In addition to TP-HTCLs, equivalent thermosetting (TS) HTCLs with an epoxy resin, Epolam, are fabricated to compare the results and evaluate the possibility of fabricating recyclable TP-FMLs at room temperature with enhanced out-of-plane properties. Impact properties including contact force, deflection, energy parameters, and related damage modes are investigated and presented for each laminate. It is concluded that the newly developed TP-HTCLs can be cured at room temperature and have enhanced impact properties compared to those of TS-HTCLs. Besides, the HTCL with UHMWPE fabrics on its composite sides (before the Ti alloy sheets) performs better in LVI compared to that with carbon fibers on the top and bottom (of its composite core) since UHMWPE exhibits higher strain to failure and fracture toughness compared to carbon fibers.

202202 bcvc ; Version of Record ; RGC ; Others ; This work was supported by Grants by National Natural Science Foundation of China ( 41901283 , 61976234 , 42071394 ), Guangdong Provincial Natural Science Foundation ( 2021A1515012567 , 2018B030312004 ), and Major Projects of High Resolution Earth Observation (Grant No. 30-H30C01-9004-19/21 ). The authors thank the Hong Kong Planning Department, Hong Kong Lands Department, the Hong Kong Civil Engineering and Development Department, the Hong Kong Observatory and the Hong Kong Government Flying Service for the planning, building GIS, weather and climate, and airborne Lidar data. Massimo Menenti acknowledges the support of grant P10-TIC-6114 by the Junta de Andalucía and the MOST High Level Foreign Expert program (Grant nr. GL20200161002 ). Man Sing Wong thanks the funding support from a grant by the General Research Fund (Grant no. 15602619 ) from the Hong Kong Research Grants Council . Dr. Qunshan Zhao has received UK ESRC's on-going support for the Urban Big Data Centre (UBDC) [ ES/L011921/1 and ES/S007105/1 ]. We would also want to thank the anonymous reviewers for their insightful comments and suggestions on an earlier version of this manuscript. ; Published

Facing severe air pollution and growing dependence on natural gas imports, the Chinese government plans to increase coal-based synthetic natural gas (SNG) production. Although displacement of coal with SNG benefits air quality, it increases CO2 emissions. Due to variations in air pollutant and CO2 emission factors and energy efficiencies across sectors, coal replacement with SNG results in varying degrees of air quality benefits and climate penalties. We estimate air quality, human health, and climate impacts of SNG substitution strategies in 2020. Using all production of SNG in the residential sector results in an annual decrease of ∼32,000 (20,000 to 41,000) outdoor-air-pollution-associated premature deaths, with ranges determined by the low and high estimates of the health risks. If changes in indoor/household air pollution were also included, the decrease would be far larger. SNG deployment in the residential sector results in nearly 10 and 60 times greater reduction in premature mortality than if it is deployed in the industrial or power sectors, respectively. Due to inefficiencies in current household coal use, utilization of SNG in the residential sector results in only 20 to 30% of the carbon penalty compared with using it in the industrial or power sectors. Even if carbon capture and storage is used in SNG production with today's technology, SNG emits 22 to 40% more CO2 than the same amount of conventional gas. Among the SNG deployment strategies we evaluate, allocating currently planned SNG to households provides the largest air quality and health benefits with the smallest carbon penalties

Facing severe air pollution and growing dependence on natural gas imports, the Chinese government plans to increase coal-based synthetic natural gas (SNG) production. Although displacement of coal with SNG benefits air quality, it increases CO2 emissions. Due to variations in air pollutant and CO2 emission factors and energy efficiencies across sectors, coal replacement with SNG results in varying degrees of air quality benefits and climate penalties. We estimate air quality, human health, and climate impacts of SNG substitution strategies in 2020. Using all production of SNG in the residential sector results in an annual decrease of ∼32,000 (20,000 to 41,000) outdoor-air-pollution-associated premature deaths, with ranges determined by the low and high estimates of the health risks. If changes in indoor/household air pollution were also included, the decrease would be far larger. SNG deployment in the residential sector results in nearly 10 and 60 times greater reduction in premature mortality than if it is deployed in the industrial or power sectors, respectively. Due to inefficiencies in current household coal use, utilization of SNG in the residential sector results in only 20 to 30% of the carbon penalty compared with using it in the industrial or power sectors. Even if carbon capture and storage is used in SNG production with today's technology, SNG emits 22 to 40% more CO2 than the same amount of conventional gas. Among the SNG deployment strategies we evaluate, allocating currently planned SNG to households provides the largest air quality and health benefits with the smallest carbon penalties

This paper offers a characterization of fundamental limits on the classification and reconstruction of high-dimensional signals from low-dimensional features, in the presence of side information. We consider a scenario where a decoder has access both to linear features of the signal of interest and to linear features of the side information signal; while the side information may be in a compressed form, the objective is recovery or classification of the primary signal, not the side information. The signal of interest and the side information are each assumed to have (distinct) latent discrete labels; conditioned on these two labels, the signal of interest and side information are drawn from a multivariate Gaussian distribution that correlates the two. With joint probabilities on the latent labels, the overall signal-(side information) representation is defined by a Gaussian mixture model. By considering bounds to the misclassification probability associated with the recovery of the underlying signal label, and bounds to the reconstruction error associated with the recovery of the signal of interest itself, we then provide sharp sufficient and/or necessary conditions for these quantities to approach zero when the covariance matrices of the Gaussians are nearly low rank. These conditions, which are reminiscent of the well-known Slepian–Wolf and Wyner–Ziv conditions, are the function of the number of linear features extracted from signal of interest, the number of linear features extracted from the side information signal, and the geometry of these signals and their interplay. Moreover, on assuming that the signal of interest and the side information obey such an approximately low-rank model, we derive the expansions of the reconstruction error as a function of the deviation from an exactly low-rank model; such expansions also allow the identification of operational regimes, where the impact of side information on signal reconstruction is most relevant. Our framework, which offers a principled mechanism to integrate side information in high-dimensional data problems, is also tested in the context of imaging applications. In particular, we report state-of-the-art results in compressive hyperspectral imaging applications, where the accompanying side information is a conventional digital photograph. ; This work was supported in part by the (PIDDAC) for Future Health/Faculdade de Engenharia da Universidade do Porto under Grant NORTE-07-0124-FEDER-000068, funded by the Fundo Europeu de Desenvolvimento Regional through the Programa Operacional do Norte, in part by the National Funds, through FCT/MEC (PIDDAC), in part by the Royal Society International Exchanges Scheme under Grant IE120996, in part by AFOSR, in part by ARO, in part by DARPA, in part by DOE, in part by NGA, and in part by ONR. F. Renna was supported by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie under Grant 655282. M. R. D. Rodrigues was supported by EPSRC under Grant EP/K033166/1.

The maritime industry is moving toward a "goal‐setting" risk‐based regime. This opens the way to safety engineers to explore and exploit flexible and advanced risk modeling and decision‐making approaches in the design and operation processes. In this article, following a brief review of the current status of maritime risk assessment, a design/operation selection framework and a design/operation optimization framework are outlined. A general discussion of control engineering techniques and their application to risk modeling and decision making is given. Four novel risk modeling and decision‐making approaches are then outlined with illustrative examples to demonstrate their use. Such approaches may be used as alternatives to facilitate risk modeling and decision making in situations where conventional techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in general engineering and technology are suggested with respect to risk modeling and decision making.

The Xuanwei area of Yunnan Province, China, is one of the regions suffering from the highest occurrence and mortality rate of lung cancer in the world. Local residents tend to use bituminous coal as domestic fuel, which causes serious indoor air pollution and is established as the main carcinogen. After the local government carried out furnace and stove reform work, lung cancer rate including incidence and mortality among residents remains high. We herein wonder if there are specific mechanisms at protein level for the development of non‐small‐cell lung cancer (NSCLC) in this area. We investigated the changes of protein profiling in tumour of the patients from Xuanwei area. Tandem mass tag (TMT) was employed to screen the differential proteins between carcinoma and para‐carcinoma tissues. We identified a total of 422 differentially expressed proteins, among which 162 proteins were significantly up‐regulated and 260 were downregulated compared to para‐carcinoma tissues. Many of the differentially expressed proteins were related to extracellular matrix (ECM)‐receptor interaction, focal adhesion, PI3K/AKT pathway and ferroptosis. Further experiments on the two differential proteins, thioredoxin 2 (TXN2) and haptoglobin (HP), showed that the change of their expressions could make the lung cancer cell lines more resistant to erastin or RSL‐induced ferroptosis in vitro, and promote the growth of tumour in nude mice. In conclusion, this study revealed that aberrant regulation of ferroptosis may involve in the development of lung cancer in Xuanwei area.