摘要 ：

Distributed hybrid energy systems are innovative means of effectively addressing energy and environmental issues in the age of carbon neutrality. This paper proposes the distributed energy hierarchical network planning model for distributed energy systems at the community level, which combines distributed energy planning and renewable energy use. This model incorporates the energy flow between nodes and line length into the optimization objective and analyzes its capability to improve the stability and cost-effectiveness of the network. A community is selected as an example, and the model is compared with single-layer network planning and node distance planning. The stability of the distributed energy hierarchical network planning model is demonstrated by the network efficiency, the node degree distribution in the low-value region and the relatively small number of effective connection edges. The total line length of the model decreases by 22% compared to the single-layer plan and by 43% compared to the node distance plan. By optimizing the topological connection structure of the network, the total length of transmission lines in energy communities can be significantly reduced, which affects line construction costs and transmission losses, and therefore, saving money on the operation and maintenance of power lines as well as management costs.

关键词 ：

Distributed energy Energy community Net-zero emissions Hierarchical network planning

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Concrete-filled square stainless steel tubes (CFSSST), which possess relatively large flexural stiffness, high corrosion resistance and require simple joint configurations and low maintenance cost, have a great potential in constructional applications. Despite that the use of stainless steel may result in high initial cost compared to their conventional carbon steel counterparts, the whole-life cost of CFSSST is however considered to be lower, which offers a competitive choice in engineering practice. In this paper, a comprehensive experimental and numerical program on 24 CFSSST stub column specimens, including 3 austenitic and 3 duplex stainless steel square hollow section (SHS) stub columns and 9 austenitic and 9 duplex CFSSST stub columns, has been carried out. Finite element (FE) models were developed to be used in parametric analysis to investigate the influence of the tube thickness and concrete strength on the ultimate capacities more accurately. Comparisons of the experimental and numerical results with the predictions made by design guides ACI 318, ANSI/AISC 360, Eurocode 4 and GB 50936 have been performed. It was found that these design methods generally give conservative predictions to the ultimate capacities of CFSSST stub columns. Improved calculation methods, developed based on the Continuous Strength Method, have been proposed to provide more accurate estimations of the ultimate resistances of CFSSST stub columns. The suitability of these proposals has been validated by comparison with the test results, where a good agreement between the predictions and the test results have been achieved. study; stub column tests

关键词 ：

concrete-filled square stainless steel tubes study Continuous Strength Method stub column tests compressive behavior parametric

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Diabetic wounds are a worldwide health problem, with increasing morbidity and risk of amputation. This study investigated a novel application of a human decellularized adipose tissue matrix (hDAM) as a natural 3D scaffold for delivering human adipose-derived stem cells (hASCs) to diabetic wounds. The porous structure, ability to preserve extracellular matrix components, and convenient storage conditions of decellularized hDAM make it a potential clinical wound dressing material. The hASCs cultured in the hDAM scaffold exhibited a fibroblast-like morphology and more evenly distributed cells on both the surface and inside the porous structure of the hDAM scaffold. In addition, the biocompatibility of hDAM enhanced the hASCs proliferation, maintenance of the stemness properties, and release of angiogenic cytokines compared to those under standard culture conditions. Moreover, cell suspensions derived from hASCs cultured in hDAM scaffolds promoted the proliferation and migration of human umbilical vascular endothelial cells, indicating its potential effect in promoting angiogenesis. Furthermore, the potential clinical therapeutic efficacy of the hASC-hDAM composite for diabetic wound healing was evaluated using a full-thickness wound model in diabetic mice. Diabetic rats treated with the hASCsseeded hDAM scaffold displayed enhanced wound healing efficiency, including an improved blood perfusion volume for wounds, reduced number of inflammatory cells, and enhanced epithelization. This study demonstrated that the 3D model that combined hASCs and an hDAM could accelerate wound healing and might hold potential for clinical application to enhance diabetic wound healing and regeneration.

关键词 ：

Human decellularized adipose tissue matrix Human adipose-derived stem cells (hASCs) (hDAM) Diabetic wound healing

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The dioxins (DXN) are a set of pollutants encompass polychlorinated dibenzo-p-dioxin/dibenzofuran (PCDD/F), their emissions from municipal waste incineration processes (MSWI) are normally detected under steady oper-ating conditions. However, limited studies have focused on the PCDD/F emission characteristics under a com-plete maintenance operating period (CMOP), which includes shut-down, cooling, maintenance, heating, startup, and normal operations. In this article, the shutdown process (SDP) starts from the normal operation, followed by shutdown, and then cooling; while the startup process (SUP) commences from heating, followed by startup, and then normal operation. The detection and analysis were conducted at the SDP and SUP stages. The PCDD/F mass and total toxic equivalent quantity (TEQ) concentrations were measured in the flue gas and bag filter fly ash (BF-FA) during a CMOP of Beijing MSWI plant. The highest PCDD/F concentrations in the flue gas were found in the "cooling" and "startup" phases; in the FA, this condition occurred in the "startup" phase. Further, the results show that the most heightened concentrations were observed for 5-6 chlorinated PCDF and 4-5 chlorinated PCDD among the 17 PCDD/F congeners in most cases. More importantly, the air pollution control devices (APCDs) which include activated carbon, lime, and BF, have high removal efficiency for PCDD/F (especially PCDD) during the "startup" phase. APCDs also easily release a considerable amount of PCDD/F because of the memory effect, which emits more PCDD/F at the "shutdown" phase than at the "startup" one. Besides, the annual PCDD/F emission in the flue gas of the MSWI plant was estimated to be 67.72 mg I-TEQ, of which the emission accounts for approx. 20% during the CMOP. Moreover, the experiment shows that the PCDD/F emissions of the MSWI plant in Beijing under unsteady conditions are more miniature than those reported earlier in other areas.

关键词 ：

Annual dioxins emission dibenzofuran (PCDD (CMOP) Memory effect Dioxin F) Polychlorinated dibenzo-p-dioxin Complete maintenance operating period Municipal solid waste incineration (MSWI)

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Vision monitoring of distress has emerged as a new trend in intelligent transportation infrastructure systems, including roads and bridges. Recently, transfer learning methods and lightweight networks have been used to realize efficient distress identification without large amount of human-labor work. This paper proposed an engineering approach that integrated transfer learning with lightweight models to classify and detect concrete bridge distresses. Two datasets named Distress Dataset of Asphalt Pavement (DDAP) with 2500 asphalt pavement distresses images and Distress Dataset of Concrete Bridge (DDCB) with 906 concrete bridge distresses images were used. The lightweight models MobileNet and MobileNet-SSD were employed to conduct 6 comparative experiments for exploring the model performance with different transfer learning modes (Mode I and II) and procedures (one-step and two-step procedure) in classification and detection tasks. Based on the comparison of the results, the optimum model for two tasks was respectively recognized. For classification task, the model directly transferred specific parameters of partial convolution layers from ImageNet-based model achieved the highest accuracy of 97.8%. For detection task, the two-step transfer learning model using an intermediate transfer learning step trained by DDAP reached a mean average precision of 87.16%. The proposed approach has the application potential for practical road inspection work in intelligent transportation infrastructure maintenance.

关键词 ：

Bridges transfer learning Convolution MobileNet-SSD Roads MobileNet distress detection Transfer learning Feature extraction Distress classification Asphalt Transportation

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Building operation and maintenance (O&M) processes are tedious. Controlling such tedious processes requires extensive visualization and trustworthy decision-making strategies. Unfortunately, challenges still exist as existing technologies and practices can hardly achieve effective control of building O&M processes. This study has established a method for achieving intelligent control of building O&M processes by integrating Global Navigation Satellite System (GNSS) with Digital Twins (DTs) techniques. Specifically, GNSS could be used to capture real-time building information during building O&M processes. Such captured real-time information realizes the intelligent closed-loop control of building O&M driven by DTs. In this study, the authors have (1) captured the dynamic information required for achieving intelligent control of building O&M processes, (2) established a DT model of building O&M processes, (3) established a data management mechanism of intelligent building O&M processes, and (4) formalized an intelligent building O&M decision control platform. Finally, the authors have validated the proposed method using the 2022 Beijing Winter Olympics venue as a case study. The three-dimensional coordinates of various building information are captured based on GNSS automatic monitoring system. This realizes the precise positioning of O&M elements and feedbacks to the twin model of the venue. Through the intelligent analysis and prediction of O&M information, the characteristics of various O&M accidents are obtained. Finally, under the navigation function of GNSS, the processing measures are accurately formulated. Results indicate that the proposed GNSS-DTs-based method could help to achieve intelligent control of large building O&M processes.

关键词 ：

operation and maintenance digital twin GNSS

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The operation and maintenance (O&M) of buildings plays an important role in ensuring that the buildings work normally, as well as reducing the damage caused by functional errors. There are obvious problems in the traditional O&M modality, and an effective way to solve them is to make the model smarter. In this paper, a digital twin framework for building operation is proposed, which consists of two key components: a digital twin O&M model and a machine learning algorithm. The process of establishing the digital twin model is introduced in detail, and the method is explained according to the structure, equipment, and energy consumption characteristics of the model. A mechanism of fusing the digital twin and machine learning algorithm is proposed and the prediction process based on an artificial neural network (ANN) is shown. Finally, based on a systematic summary of the modeling process and fusion mechanism, the development path and overall structure of the intelligent O&M system utilizing digital twins is proposed.

关键词 ：

artificial neural network machine learning digital twin operation and maintenance

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Flange connections are widely used in various mechanical components. The most important purpose of tightening for flanged bolts is to achieve designed clamping force for the maintenance of overall performance. In this work, a multi-bolt tightening algorithm is proposed based on elastic interaction coefficient and gasket creep relaxation. Firstly, dispersion of the individual bolt clamping forces for torque control method is considered in the algorithm. Relationship between the nut factors of the flange bolts in multi-pass tightening is established through experiment. Subsequently, the elastic interaction coefficient matrix was updated during the multi-pass tightening process to reduce the error. Two cases, without gasket and silicone gasket, are considered in the multi-bolt tightening experiment. Without gasket, the elastoplastic deformation at the initial stage after tightening will also cause a loss of clamping force. When using gasket, the clamping force loss due to gasket creep relaxation is more pronounced. Through experimental verification, the proposed multi-bolt tightening algorithm are able to achieve the target range of designed clamping forces and reduce its dispersion. Finally, the main influencing factors of the multi-bolt tightening are analyzed to provide a reference for the design of flange connections.

关键词 ：

elastic interaction coefficient multi-bolt tightening creep relaxation tightening algorithm

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China fully built a wealthy society but faced a serious COVID-19 epidemic together with the rest of the world. The emergence of the epidemic highlights the importance of sports parks for physical activity. By reviewing national fitness policies and identifying several types of sports parks, this paper investigates urban dwellers' usage and preferences in sports parks by means of a questionnaire, with behavioural observation and interviews as complementary research methods. Taking the Beijing Olympic Forest Park, Sun Park, and Huilongguan Park as examples, this study reveals that participants present a high overall satisfaction with the sports parks. The factor analysis indicates that Sports Facilities and Maintenance & Management are the first and second most significant factors influencing residents' willingness to use sports parks. This research can guide the planning and construction of sports park in the future.

关键词 ：

sports parks post-occupancy evaluation semantic differential method

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Pavement marking in daylight with poor quality cannot provide a reference for drivers to specify their own position relative to nearby vehicles. Luminance and Correlated color temperature (CCT) of sunlight is of importance for daytime visibility of in-service pavement markings, which lacks detailed consideration. This paper aims to explore the daytime visibility requirements of in-service pavement markings considering the influence of natural light characteristics. Based on analyzing the mechanism and impact factors of daytime visibility of pavement markings, a subjective scale of pavement markings state in the drivers' field of view was proposed and a short and bold line was recommended as the standard state. Thirty-six tested drivers were randomly selected to detect white and yellow markings of both 15 cm and 20 cm width under 2000 to 23,000 lx and 5500 to 8500 K for outdoor natural light environment. The luminance contrast of the pavement marking to the surrounding road surface ranged from 0 to 10. The result indicated that the natural light with 2000 to 3000 lx and 7500 to 8500 K is the most unfavorable light environment for drivers to recognize pavement markings during daytime. The detection distance is becoming longer with the increase of luminance contrast. The detection distance does not increase with the increase of luminance contrast when the luminance contrast of white markings is greater than 4 and that of yellow markings is greater than 3. The model was established expressing the relationship between luminance contrast and Q(d) contrast. The preview time 3.65 s was selected to calculate the minimum requirements of Q(d) at speeds of 60, 80, 100 km/h, respectively, for different types of markings. The results can provide scientific evidence for quality evaluation and maintenance management of pavement markings in service for daytime visibility.

关键词 ：

daytime visibility detection distance pavement markings luminance contrast

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