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Abstract Organic solar cells (OSCs) are considered as a crucial energy source for flexible and wearable electronics. Pseudo-planar heterojunction (PPHJ) OSCs simplify the solution preparation and morphology control. However, non-halogenated solvent-printed PPHJ often have an undesirable vertical component distribution and insufficient donor/acceptor interfaces. Additionally, the inherent brittleness of non-fullerene small molecule acceptors (NFSMAs) in PPHJ leads to poor flexibility, and the NFSMAs solution shows inadequate viscosity during the printing of acceptor layer. Herein, we propose a novel approach termed polymer-incorporated pseudo-planar heterojunction (PiPPHJ), wherein a small amount of polymer donor is introduced into the NFSMAs layer. Our findings demonstrate that the incorporation of polymer increases the viscosity of acceptor solution, thereby improving the blade-coating processability and overall film quality. Simultaneously, this strategy effectively modulates the vertical component distribution, resulting in more donor/acceptor interfaces and an improved power conversion efficiency of 17.26%. Furthermore, PiPPHJ-based films exhibit superior tensile properties, with a crack onset strain of 12.0%, surpassing PPHJ-based films (9.6%). Consequently, large-area (1 cm2) flexible devices achieve a considerable efficiency of 13.30% and maintain excellent mechanical flexibility with 82% of the initial efficiency after 1000 bending cycles. These findings underscore the significant potential of PiPPHJ-based OSCs in flexible and wearable electronics.

Abstract As China has entered a new stage of high-quality development, clarifying the mechanism and spatial characteristics of green development for urban agglomerations are critical to sustainable development. Based on the data of 11 major cities in the Harbin-Changchun urban agglomeration (HCUA) from 2010 to 2020, this study constructs an evaluation system of green development index (GDI) is composed of four dimensions, i.e. urban green construction (UGC), industrial green development (IGD), resource and environmental carrying capacity (RECC), and technological innovation support (TIS). Furthermore, using the entropy weight method to obtain the weights of evaluation indicators. And then, the comprehensive index calculation is used to evaluate the GDI. The driving factors of each level of GDI are determined by the Pearson correlation coefficient. The results infer some novel findings as follows: (1) the overall tendency of the GDI of the HCUA has gradually increased from 0.358 in 2010 to 0.379 in 2020 which is at the average level. The dimension of TIS shows the highest rate of contribution while IGD and RECC show a fluctuating trend over the time window. (2) The GDI in the HCUA exhibits a patchy clustering differentiation feature that spreads from the central area to the surrounding areas with a “high in the south and low in the north” pattern. Specifically, Changchun, Harbin, and Daqing form an “inverted triangle” structure in geographical location to drive the green development of neighboring areas. (3) The core cities of the HCUA, Changchun, and Harbin, show a much higher level than the other cities. Jilin and Daqing are at the average level, and besides, the rest of the cities of GDI are at the poor level with significant fluctuations in ranking. (4) There are different driving factors between each level of GDI. For cities with good and average levels should focus on protecting resources and the environment. Meanwhile, cities with poor level of GDI need to improve IGD to optimize the urban green structure. Thus, it is suggested to strengthen the flow of factors and implement differentiated strategies to promote coordinated development and spatial clustering.

After a period of rapid development, the process of urbanization in China has gradually shifted from “scale expansion” to “enhanced quality”. The scarcity of urban land resources has created constraints on resources and economic development. This paper examines the carrying capacity of urban land resources from the perspective of urban renewal. A conceptual model of the driving mechanism of land comprehensive carrying capacity is constructed, incorporating six dimensions and 22 indicators, including urban renewal and urban ecology. Through questionnaire surveys and structural equation modeling, feedback data are analyzed, and measurement models, structural models, and mediation effects are examined to analyze the causal paths of factors in different dimensions on the comprehensive carrying capacity of urban land. The research results indicate that all six dimensions in the conceptual model have a direct positive impact on the land carrying capacity. In terms of direct effects, the influencing factors are ranked in descending order of magnitude as follows: urban development, urban disaster prevention and mitigation capacity, infrastructure development, urban renewal, social economy, and urban ecology. In terms of overall effects, factors are ranked in descending order of magnitude as follows: urban development, social economy, urban ecology, urban renewal, urban disaster prevention and mitigation capacity, and infrastructure development.

The orientation of layered perovskites plays a crucial role in their charge transport behavior and hence, the efficiency of related solar cells. Here, the authors find that preformed 3D-like perovskites can efficiently template the growth of layered perovskites and determine their orientation.

Safety risk assessment is essential in ensuring the smooth construction of undersea tunnels. Obtaining reasonable safety risk assessment results requires multi-source information that enjoys static and dynamic attributes. However, acquiring and utilizing such uncertain information creates difficulties in the decision-making process. Therefore, this paper proposes a safety risk assessment approach based on building information modeling (BIM), intuitionistic fuzzy set (IFS) theory, and Dempster–Shafer (D-S) evidence theory. Firstly, an undersea tunnel construction collapse risk evaluation index system is established to clarify the information requirements of the pre-construction and construction stages. The semantic information of the BIM geometric model is then enriched through industry foundation classes (IFC) extension to match the multi-criteria decision-making (MCDM) process, with BIM technology used to assist in information acquisition and risk visualization. Finally, based on the intuitionistic fuzzy D-S evidence theory, multi-information fusion is performed to dynamically determine safety risk levels. Specifically, IFS theory is utilized for basic probability assignments (BPAs) determination before applying D-S evidence theory. The conflicting evidence is dealt with by reliability calculation based on the normalized Hamming distance between pairs of IFSs, while safety risk levels are accomplished with score functions of intuitionistic fuzzy values (IFVs). The proposed method is applied to collapse risk assessment in the karst developed area of a shield tunnel construction project in Dalian, China, and the feasibility and effectiveness are verified. The novelty of the proposed method lies in: (1) information collaboration between the BIM model and the dynamic safety risk assessment process being realized through IFC-based semantic enrichment and Dynamo programming to enhance the decision-making process and (2) the introduction of IFS theory to improve the applicability of D-S evidence theory in expressing fuzziness and hesitation during multi-information fusion. With the proposed method, dynamic safety risk assessment of undersea tunnel construction projects can be performed under uncertainty, fuzziness, and a conflicting environment, while the safety risk perception can be enhanced through visualization.

The development of green residences is crucial to reducing energy consumption and carbon emissions of the construction industry. However, the study on the spatial distribution characteristics of green residences and its influencing factors has not attracted enough attention in the academic circles. Base on the panel database on the number of each star green residences and their driving factors at the municipal level from 2008 to 2016, this paper employed the Weighted Standard Deviational Ellipse model to reveal the spatial and temporal evolution features of green residences in China, creatively introduced an improved Gini coefficient (G′-score) to measure the green residences development in each city, and utilized the panel Tobit model and average marginal effect to identify the driving mechanisms and key factors of green residences from economy, society, the real estate market, policy and climate. The main conclusions show that: (1) China has formed a relatively stable and clear temporal and spatial evolution path since 2011, such as the center of gravity and coverage having moved to the west, and the direction of development trend having weakened; (2) China’s green residence is mainly distributed in the central and eastern regions, and the main direction layout is northeast–southwest; (3) the development of green residences is the result of the interaction of various factors, and the driving force of each factor varies greatly under the single action and the interaction; (4) the driving effects of the same factor on green residences with different star ratings are inconsistent in sign, magnitude, and significance, the same as for each factor under the same star rating.

Optoelectronic devices based on organic–inorganic halide perovskites show promising performance, but their poor stability impedes the commercialization. Here Lin et al. show that excess free charges are detrimental and efficient charge-carrier extraction is necessary for improved device stability.

Pavement management, which is vital in road transportation and maintenance, is facing some troubles, such as high costs of labors and machineries, low detecting efficiency, and low update rate of pavement conditions by means of traditional detection ways. Benefiting from the development of mobile communication, mobile computing, and mobile sensing techniques, the intelligence of mobile crowd sensing (MCS), which mainly relies on ubiquitous mobile smart devices in people’s daily lives, has overcome the above drawbacks to a large extent as one new effective and simple measure for pavement management. As a platform for data collection, processing, and visualization, a common smart device can utilize inertial sensor data, photos, videos, subjective reports, and location information to involve the public in pavement anomalies detection. This paper systematically reviewed the studies in this field from 2008 to 2018 to establish an overall knowledge. Through literature collection and screening, a database of studies was set up for analysis. As a result, the year profile of publications and distribution of research areas indicate that there has been a constant attention from researchers in various disciplines. Meanwhile, the distribution of research topic shows that inertial sensors embedded in smartphones have been the most popular data source. Therefore, the process of pavement anomalies detection based on inertial data was reviewed in detail, including preparatory, data collection, and processing phases of the previous experiments. However, some of the key issues in the experimental phases were investigated by previous studies, while some other challenges were not tackled or noticed. Hence, the challenges in both experiment and implementation stages were discussed to improve the studies and practice. Furthermore, several directions for future research are summarized from the main issues and challenges to offer potential opportunities for more relevant research studies and applications in pavement management.

As a revolutionary technology, terrestrial laser scanning (TLS) is attracting increasing interest in the fields of architecture, engineering and construction (AEC), with outstanding advantages, such as highly automated, non-contact operation and efficient large-scale sampling capability. TLS has extended a new approach to capturing extremely comprehensive data of the construction environment, providing detailed information for further analysis. This paper presents a systematic review based on scientometric and qualitative analysis to summarize the progress and the current status of the topic and to point out promising research efforts. To begin with, a brief understanding of TLS is provided. Following the selection of relevant papers through a literature search, a scientometric analysis of papers is carried out. Then, major applications are categorized and presented, including (1) 3D model reconstruction, (2) object recognition, (3) deformation measurement, (4) quality assessment, and (5) progress tracking. For widespread adoption and effective use of TLS, essential problems impacting working effects in application are summarized as follows: workflow, data quality, scan planning, and data processing. Finally, future research directions are suggested, including: (1) cost control of hardware and software, (2) improvement of data processing capability, (3) automatic scan planning, (4) integration of digital technologies, (5) adoption of artificial intelligence.

Integrated Project Delivery (IPD) has become increasingly popular in the architecture, engineering, and construction industries. However, the current practice status by the construction industry fails to deliver the desired results. In that backdrop, how to promote cooperation within and improve the overall performance of integrated project team has received wide attention. Herein, knowledge-sharing plays a critical role in cooperation and overall performance. However, to the best of our knowledge, the research on knowledge-sharing strategy interaction and evolutionary mechanism is rare. To make up for the deficiency of the studies existing, a novel model is proposed by taking advantage of evolutionary game theory, to capture the interaction behavior of knowledge-sharing and explore its evolutionary mechanism. Six parameters of knowledge stock, knowledge-sharing degree, heterogeneous knowledge proportion, synergy effect, knowledge absorption coefficient, and knowledge-sharing cost efficient that are critical to knowledge-sharing are extracted and defined. The payoff matrix is constructed by analyzing the benefits and costs of knowledge-sharing. Then, a replicator dynamic system is established based on payoff matrix, to determine the evolutionary tendency of knowledge-sharing behavior. Finally, numerical simulations are conducted to explore the influences of all parameters on the knowledge-sharing strategy. The findings in this research reveal that strategy interaction behavior is significantly influenced by proportion of strategy of choosing to share knowledge in both game players. The authors also find that strategy interaction behavior has a strong negative correlation with knowledge-sharing cost efficient, but has a positive correlation with knowledge stock, heterogeneous knowledge proportion, degree of knowledge-sharing, knowledge absorption coefficient, and synergetic effect coefficient. This research can provide the evolutionary mechanism and broaden our understanding of relationship between project performance and knowledge-sharing and can offer valuable guidance on improving cooperation and performance of project teams.

An effective evaluation model for safety appraisal of existing concrete members plays a significant role in promoting the management of an existing building. This study aims to introduce extension theory into the safety appraisal of existing concrete members based on five indices (bearing capacity, deflection-to-span ratio, cracks, reinforcement corrosion, and concrete carbonation depth) and inspection data. A matter-element model is established for the safety appraisal of existing concrete members based on matter-element theory. The safety appraisal rating is identified by the comprehensive correlation degrees, which can be calculated by the weights and single-index correlation degrees of the five indices. Owing to the one-sidedness in the single-weighting method, a comprehensive weighting method integrating the merits of subjective weight and objective weight is adopted based on game theory. The interval analytic hierarchy process (IAHP) and entropy weight method are, respectively, used to determine the subjective and objective weight of each index. It was found that the subjective weight vector calculated by IAHP consists of interval numbers. Therefore, the traditional comprehensive weighting method based on game theory needs to be improved by the interval number theory. A comparison analysis between the results generated by the proposed model and an analytic hierarchy process-fuzzy comprehensive evaluation model is conducted. The results show that the matter-element extension model based on comprehensive weight is more accurate and rational. The proposed model makes full use of inspection data and gives a clear safety level to decision makers avoiding disorganized data of a single index. Hence, it can serve as guidance for safety appraisal of existing concrete members in the future. Furthermore, the improved comprehensive weighting method has practical merits and high scientific value in terms of safety evaluation and other applications in different research fields.

Tower cranes are the most commonly used large-scale equipment on construction site. Because workers can’t always pay attention to the environment at the top of the head, it is often difficult to avoid accidents when heavy objects fall. Therefore, safety construction accidents such as struck-by often occurs. In order to address crane issue, this research recorded video data by a tower crane camera, labeled the pictures, and operated image recognition with the MASK R-CNN method. Furthermore, The RGB color extraction was performed on the identified mask layer to obtain the pixel coordinates of workers and dangerous zone. At last, we used the pixel and actual distance conversion method to measure the safety distance. The contribution of this research to safety problem area is twofold: On one hand, without affecting the normal behavior of workers, an automatic collection, analysis, and early-warning system was established. On the other hand, the proposed automatic inspection system can help improve the safety operation of tower crane drivers.

In construction projects, the planning objectives include the safety and labor productivity of the activities, along with the cost influence affecting the overall performance of construction. Temporary facilities are critical in supporting structures and equipment that impact the direct task executions and resource transportation during various construction stages. The positioning of temporary facilities and the relative spatial relation between multiple facilities are critical factors that affect the success of construction delivery. To ensure the balance among safety, labor productivity and construction cost performance, all influencing factors associated with the construction objectives should be taken into account in temporary facility layout planning. This paper proposes a novel multi-criteria temporary facility layout planning model that integrates Analytic Network Process (ANP) modeling and simulation-based sensitivity evaluation, which effectively transforms the spatial layout planning problem into a mathematical decision problem. An application example is analyzed to demonstrate its capabilities of optimizing temporary facility layout planning. The proposed framework provides the construction managers and layout planners with a useful tool for selecting the optimal alternative of temporary facility layout plan on the construction site.

An effective forecasting model for short-term load plays a significant role in promoting the management efficiency of an electric power system. This paper proposes a new forecasting model based on the improved neural networks with random weights (INNRW). The key is to introduce a weighting technique to the inputs of the model and use a novel neural network to forecast the daily maximum load. Eight factors are selected as the inputs. A mutual information weighting algorithm is then used to allocate different weights to the inputs. The neural networks with random weights and kernels (KNNRW) is applied to approximate the nonlinear function between the selected inputs and the daily maximum load due to the fast learning speed and good generalization performance. In the application of the daily load in Dalian, the result of the proposed INNRW is compared with several previously developed forecasting models. The simulation experiment shows that the proposed model performs the best overall in short-term load forecasting.

An innovative logic tree, Failure Expansion Tree (FET), is proposed in this paper, which improves on traditional Fault Tree Analysis (FTA). It describes a different thinking approach for risk factor identification and reliability risk assessment. By providing a more comprehensive and objective methodology, the rather subjective nature of FTA node discovery is significantly reduced and the resulting mathematical calculations for quantitative analysis are greatly simplified. Applied to the Useful Life phase of a subsea pipeline engineering project, the approach provides a more structured analysis by constructing a tree following the laws of physics and geometry. Resulting improvements are summarized in comparison table form.

For reliability testing an Energy Expansion Tree (EET) and a companion Energy Function Model (EFM) are proposed and described in this paper. Different from conventional approaches, the EET provides a more comprehensive and objective way to systematically identify external energy factors affecting reliability. The EFM introduces energy loss into a traditional Function Model to identify internal energy sources affecting reliability. The combination creates a sound way to enumerate the energies to which a system may be exposed during its lifetime. We input these energies into planning an accelerated life test, a Multi Environment Over Stress Test. The test objective is to discover weak links and interactions among the system and the energies to which it is exposed, and design them out. As an example, the methods are applied to the pipe in subsea pipeline. However, they can be widely used in other civil engineering industries as well. The proposed method is compared with current methods.

As a mean of supplying water, Water distribution system (WDS) is one of the most important complex infrastructures. The stability and reliability are critical for urban activities. WDSs can be characterized by networks of multiple nodes (e.g. reservoirs and junctions) and interconnected by physical links (e.g. pipes). Instead of analyzing highest failure rate or highest betweenness, reliability of WDS is evaluated by introducing hydraulic analysis and cascading failures (conductive failure pattern) from complex network. The crucial pipes are identified eventually. The proposed methodology is illustrated by an example. The results show that the demand multiplier has a great influence on the peak of reliability and the persistent time of the cascading failures in its propagation in WDS. The time period when the system has the highest reliability is when the demand multiplier is less than 1. There is a threshold of tolerance parameter exists. When the tolerance parameter is less than the threshold, the time period with the highest system reliability does not meet minimum value of demand multiplier. The results indicate that the system reliability should be evaluated with the properties of WDS and the characteristics of cascading failures, so as to improve its ability of resisting disasters.

As a radically distinct wireless communication approach compared to traditional narrow band systems, ULTRA-WIDE BAND (UWB) technology has been applied in various sectors and is gaining in popularity, but there appears to be a lack of systematic summary of the potential of this technology. To provide insights into UWB technology for the uninitiated reader, this paper explores the state-of-the-art research and development of UWB applications in many sectors including the construction industry without concerning the technological details. First this paper presents the key concepts related to UWB technology and a brief history of UWB. Then it summarizes the UWB's technical features which enable its popularity in industry. Finally, application examples of UWB technology in many sectors, including construction, are presented to analyze and highlight the impact on the industry performance. In the near future UWB technology is expected to become a very important component and have far-reaching impact in ubiquitous computing. Santrauka Bevielio ryšio ultraplačios juostos bangų (UWB) technologija, radikaliai besiskirianti nuo tradicinės siauros juostos sistemų, buvo plačiai taikoma įvairiuose sektoriuose ir tampa vis populiaresnė, tačiau akivaizdu, kad vis dar trūksta susistemintos šios technologijos galimybių apžvalgos. Siekiant pateikti įžvalgas apie UWB technologiją, šiame straipsnyje analizuojami dabartiniai UWB technologijos tyrimai ir UWB taikymas įvairiuose sektoriuose, įskaitant statybą, nenagrinėjant technologinių detalių. Pirmiausia šiame straipsnyje pristatomos pagrindinės sąvokos, susijusios su UWB technologija ir UWB technologijos istorine raida. Tada susisteminamos techninės UWB technologijos charakteristikos, kurios lemia jos populiarumą pramonėje. Galiausiai analizuojami UWB technologijos taikymo pavyzdžiai įvairiuose sektoriuose, įskaitant statybą, atkreipiant dėmesį į jų poveikį pramonės veiklai. Netolimoje ateityje UWB technologija turėtų tapti labai svarbi ir turėti ilgalaikį poveikį visuotinei kompiuterizacijai. Reikšminiai žodžiai: ultraplačios juostos bangos, dažnio svyravimai, gavėjas, sekimas, jutimas, statybos pramonė