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A Plasticity Theory Approach for the Stability Analysis of Vertical Layers of Concrete in the Fresh State
No full textThe industrial production of cement is currently responsible for around 5% of global CO2 emissions. Hence, the development of technologies aimed at minimizing the use of cement in concrete structures, while preserving their strength and durability properties, plays a vital role in the reduction of carbon emissions. The use of cement in concrete structures can be minimized through the manufacture of functionally layered structural elements where concrete with high cement content is used rationally only when it contributes significantly to the performance of the structure. In functionally layered concrete, horizontal variation in material composition can be achieved by casting adjacent vertical layers of different materials. Removable vertical panels can be used to demarcate the mixes during casting. A good bond between the layers can be achieved by removing the panels prior to concrete hardening. However, a major problem with this application is the control of the fresh-state deformations of the adjacent vertical layers. This study investigates the fundamental problem of fresh state stability of concrete prisms that consist of two vertical layers of different mixes. A novel limit-state approach based on plasticity theory is formulated to assess the stability of the system as a function of material properties and geometry. The relationship between material parameters, system stability and geometry is determined and the formulated limit-state approach is validated against experimental results
Energy assessment and economic sensitivity analysis of a grid-connected photovoltaic system
No full textThis paper presents techno-economic assessment results of a grid-connected photovoltaic (PV) system for domestic building application. The PV system electricity output, energy conversion efficiency and cell temperature are explored based on the local weather condition, the system life cycle cost is evaluated with full account of the life of assets, volatile economic fluctuations, uncertainty influence factors, net present value (NPV) and discounted payback period (DPP) under Feed-in Tariff (FiT) scheme, the annual savings and payback time are compared for the FiT and new Smart Export Guarantee (SEG) schemes. Technical analysis results indicate that the system is capable of fulfilling the building electrical energy demand from April to October, and the extra electricity of 1530.23 kWh is exported to the grid in this period. The life cycle cost assessment results illustrate that the system achieves a NPV of £1335.32 and has a DPP of 9.34 years under the FiT scheme. Moreover, the sensitive analyses reveal that the high discount rate decreases the system NPV whereas the high initial cost leads to long payback period to realize the positive NPV. Furthermore, the FiT is the most cost-effective solution for PV system and has the shortest DPP compared with the SEG
Experimental validation of a hybrid FE-SEA-experimental model
No full textModern manufacturers usually need to know at a design stage if their products will meet certain vibro-acoustic requirements. In many cases the use of physical prototyping becomes significantly expensive, and engineers opt for the development of predictive computational models. In these cases, a hybrid deterministic-statistical approach can overcome the challenges that arise when predicting the response of built-up systems in the mid-frequency range. These models, however, may face limitations when complex vibration sources need to be considered. These limitations were recently addressed using a hybrid statistical-experimental model for the case where the vibration sources are directly coupled to statistical components. In this work the approach is extended to the more realistic scenario where the structure of interest contains also deterministic components. The approach is tested in a laboratory case study consisting of a complex vibration source, rigid beams, and a statistical plate receiver. The developed model is validated by comparing the predicted vibration response to the one obtained by experimentally randomising the receiver plate. The results show that a good agreement is obtained for the statistics of the response of not only the statistical plate receiver, but also the deterministic rigid beams. It is concluded that FE-SEA-experimental models can be a suitable tool for predicting the statistics of the response of complex systems
The obstacles of China’s intelligent automobile manufacturing industry development: A structural equation modeling study
No full textPurpose: This paper aims to make a systematic study on the factors that hinder the development of China’s intelligent automobile manufacturing industry; based on comprehensive understanding of these obstacles and by optimization means, ultimately, the healthy and sustainable development of intelligent automobile manufacturing industry in China can be promoted. Design/methodology/approach: Based on a questionnaire survey of intelligent automobile manufacturing listed companies in China, first, fuzzy semantic scale was adopted to collect respondents’ choices, the fuzzy score function is used to calculate the fuzzy score value and these data are used as the basis for subsequent model analysis. Then, structural equation modeling (SEM) was adopted to analyze the causal relationship between influencing factors to explore the main hinder factors. Findings: It is found that, in the short term, the backwardness of technological industrialization is the main reason leading to low permeability of intelligent automobile; in the medium term, the imperfect industrial R&D ability and the insufficiency of infrastructure are major causes for high manufacturing cost and low competitiveness of intelligent automobile manufacturing industry; in the long term, the lack of national policy and industrial strategic planning is the main factors affect intelligent automobile manufacturing cost and the industry competitiveness. Practical implications: The research conclusion has important policy implications for promoting intelligent automobile manufacturing sustainable development. In recent years, China’s intelligent automobile manufacturing industry has gradually stepped out of breeding period; therefore, the role of government should be gradually transformed from participants to managers and regulators. Considering the fact that intelligent automobile cost is very high, and still higher than the cost of fuel vehicle, government should focus on the issues such as improving R&D capabilities, infrastructure construction, policy framework system, legal system and technological industrialization. Specifically, in short-term planning, improving technological industrialization level is the key to development; in medium-term planning, policymakers should focus on the improvement of R&D capabilities and infrastructure; considering the long-term development, establishing appropriate national policies and dealing with the adverse impact of imperfect strategic planning are the most sensible choice. Originality/value: This paper analyzes the factors that hinder the development of China’s intelligent automobile manufacturing industry for the first time, and provides the basic logic of integration factors at different levels with the development of intelligent automobile to reveal the uniqueness and facts of China’s economic development
Enhancement-Mode PEDOT:PSS Organic Electrochemical Transistors Using Molecular De-Doping
No full textOrganic electrochemical transistors (OECTs) show great promise for flexible, low-cost, and low-voltage sensors for aqueous solutions. The majority of OECT devices are made using the polymer blend poly(ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), in which PEDOT is intrinsically doped due to inclusion of PSS. Because of this intrinsic doping, PEDOT:PSS OECTs generally operate in depletion mode, which results in a higher power consumption and limits stability. Here, a straightforward method to de-dope PEDOT:PSS using commercially available amine-based molecular de-dopants to achieve stable enhancement-mode OECTs is presented. The enhancement-mode OECTs show mobilities near that of pristine PEDOT:PSS (≈2 cm2 V−1 s−1) with stable operation over 1000 on/off cycles. The electron and proton exchange among PEDOT, PSS, and the molecular de-dopants are characterized to reveal the underlying chemical mechanism of the threshold voltage shift to negative voltages. Finally, the effect of the de-doping on the microstructure of the spin-cast PEDOT:PSS films is investigated
High temperature lead-free BNT-based ceramics with stable energy storage and dielectric properties
No full textHigh-temperature dielectric ceramics are in urgent demand due to the rapid development of numerous emerging applications. However, producing dielectric ceramics with favorable temperature, frequency and electric field stability is still a huge challenge. The construction of multi-phase coexistence material systems is an effective way to obtain stable dielectric and energy storage properties. In this work, NaNbO3 (NN) modified 0.95Bi0.5Na0.5TiO3-0.05SrZrO3 (BNTSZ) ceramics ((1 - x)BNTSZ-xNN) are designed to achieve the coexistence of rhombohedral and tetragonal phases. The variation in the dielectric permittivity of the 0.8BNTSZ-0.2NN ceramic is less than ±15% over the temperature range from -55 °C to 545 °C, which is the reported record-high upper operating temperature, with a high room-temperature dielectric permittivity of 1170. The 0.8BNTSZ-0.2NN ceramic exhibits excellent frequency and electric field stability as well. Additionally, a large discharge energy density of 3.14 J cm-3 is obtained in the 0.85BNTSZ-0.15NN ceramic with an energy efficiency of 79% at a high temperature of 120 °C under 230 kV cm-1, with the variation in the discharge energy density being less than ±4% in the temperature range from 25 °C to 180 °C under 120 kV cm-1. All these features demonstrate that the (1 - x)BNTSZ-xNN ceramics are promising candidates for use at extremely high temperature in both dielectric and energy storage capacitor applications
Essential work of fracture assessment of acrylonitrile butadiene styrene (ABS) processed via fused filament fabrication additive manufacturing
No full textExperiments and finite element (FE) calculations were performed to study the raster angle–dependent fracture behaviour of acrylonitrile butadiene styrene (ABS) thermoplastic processed via fused filament fabrication (FFF) additive manufacturing (AM). The fracture properties of 3D-printed ABS were characterized based on the concept of essential work of fracture (EWF), utilizing double-edge-notched tension (DENT) specimens considering rectilinear infill patterns with different raster angles (0°, 90° and + 45/− 45°). The measurements showed that the resistance to fracture initiation of 3D-printed ABS specimens is substantially higher for the printing direction perpendicular to the crack plane (0° raster angle) as compared to that of the samples wherein the printing direction is parallel to the crack (90° raster angle), reporting EWF values of 7.24 kJ m−2 and 3.61 kJ m−2, respectively. A relatively high EWF value was also reported for the specimens with + 45/− 45° raster angle (7.40 kJ m−2). Strain field analysis performed via digital image correlation showed that connected plastic zones existed in the ligaments of the DENT specimens prior to the onset of fracture, and this was corroborated by SEM fractography which showed that fracture proceeded by a ductile mechanism involving void growth and coalescence followed by drawing and ductile tearing of fibrils. It was further shown that the raster angle–dependent strength and fracture properties of 3D-printed ABS can be predicted with an acceptable accuracy by a relatively simple FE model considering the anisotropic elasticity and failure properties of FFF specimens. The findings of this study offer guidelines for fracture-resistant design of AM-enabled thermoplastics
Life cycle assessment of lithium nickel cobalt manganese oxide (NCM) batteries for electric passenger vehicles
No full textThis study evaluated and quantified the life cycle environmental impacts of lithium-ion power batteries (LIBs) for passenger electric vehicles to identify key stages that contribute to the overall environmental burden and to find ways to reduce this burden effectively. Primary data for the assessment were collected onsite from the two Chinese leading LIB suppliers, two leading cathode material producers and two battery recycling corporations from 2017 to 2019. Six environmental impact categories, including primary energy demand (PED), global warming potential (GWP), acidification potential (AP), photochemical oxidant creation potential (POCP), eutrophication potential (EP) and human toxicity potential (HTP), were considered in accordance with the ISO 14040/14044 standards. The results indicate that material preparation stage is the largest contributor to the LIB's life cycle PED, GWP, AP, POCP, EP and HTP, with the cathode active material, wrought aluminum and electrolytes as the predominant contributors. In the production stage, vacuum drying and coating and drying are the two main processes for all the six impact categories. In the end-of-life stage, waste LIBs recycling could largely reduce the life cycle POCP and HTP. Sensitivity analysis results depict that replacing NCM 622 by NCM 811 as the cathode active material could increase all the six environmental impacts. We hope this study is helpful to reduce the uncertainties associated with the life cycle assessment of LIBs in existing literatures and to identify opportunities to improve the environmental performance of LIBs within the whole life cycle
Einsum networks: Fast and scalable learning of tractable probabilistic circuits
No full textProbabilistic circuits (PCs) are a promising avenue for probabilistic modeling, as they permit a wide range of exact and efficient inference routines. Recent “deep-learning-style” implementations of PCs strive for a better scalability, but are still difficult to train on real-world data, due to their sparsely connected computational graphs. In this paper, we propose Einsum Networks (EiNets), a novel implementation design for PCs, improving prior art in several regards. At their core, EiNets combine a large number of arithmetic operations in a single monolithic einsum-operation, leading to speedups and memory savings of up to two orders of magnitude, in comparison to previous implementations. As an algorithmic contribution, we show that the implementation of Expectation-Maximization (EM) can be simplified for PCs, by leveraging automatic differentiation. Furthermore, we demonstrate that EiNets scale well to datasets which were previously out of reach, such as SVHN and CelebA, and that they can be used as faithful generative image models
α-Stable lévy state-space models for manoeuvring object tracking
No full textIn this paper we present multidimensional α-stable state-space models for object tracking, expressed in continuous time as Lévy processes. In contrast with the conventional Gaussian models, these heavy-tailed α-stable models are more likely to exhibit extreme noise values, thus showing the capability for modeling of erratic manoeuvring behaviour. Despite the potential benefits, such models are usually highly intractable for inference and therefore have not yet been widely adopted in the tracking field. Here the models are represented in a conditionally Gaussian series form, so that the marginal (Rao-Blackwellised) particle filter can be employed to perform tracking and smoothing very efficiently. As the result, the simulation tracks present some sharp manoeuvres, owing to the heavy-tailed property, and experiments demonstrate improved performance on an intent inference problem from automotive UI with highly perturbed pointing data