Search Results (87)

With the continuous increase in the penetration rate of renewable energy, the randomness and flexibility demand in the power system continues to increase. The main grid side of the power system vigorously develops pumped hydro storage (PHS) resources. However, the current PHS station scheduling method of a fixed time period and fixed power has lost a certain flexibility supply. In this paper, an optimal dispatching model of multi-pumped hydro storage stations is proposed to supply flexibility for different regions of the state grid in east China. Firstly, the credible predictable power (CPP) of renewable energy is calculated and the definition of flexibility demand of a power system is given. The calculation model for flexibility demand is established. Secondly, considering the regional allocation constraint in the state grid in east China, a non-centralized model of multi-PHS within the dispatch scope is established. In the model, the constraints of storage capacity of different hydropower conversion coefficients of each PHS station is considered. The flexibility supply model of PHS stations to each region of the state grid in east China is established to realize reasonable flexibility allocation. Then, by combining the PHS station models and the flexibility demand calculation model, the optimal dispatching model for the flexibility supply of multi-PHS stations is established. Finally, based on the network dispatching example, the effectiveness and superiority of the proposed strategy are verified by a case study. Full article

Controlling the total amount of river pollutant discharge is an important means of water resource protection and management, and it is also a necessary condition for ensuring the normal functioning of water areas. The total amount of pollutant discharge is closely related to the water environmental capacity (WEC). Shifting from the traditional method of calculating WEC to dynamic analyses and calculations, concerning practical applications, in this paper, a dynamic adaptive calculation method is proposed for the river WEC that considers the changes in adaptive demand and hydrological conditions. In this method, the dynamic WEC is represented by intervals based on dynamic changes in different spatial and temporal scales, various calculation methods, hydrological conditions, and parameters. According to the calculation results for the WEC, a variable interval was formed. Taking the Shaanxi section of the main stream of the Wei River as the research object, with the support of an integrated platform, the dynamic adaptive calculation of the WEC in the Shaanxi section of the Wei River was realized, and a corresponding simulation system was constructed. The verification results show that (1) the dynamic calculation of WEC can be realized by freely combining different model methods and calculation conditions; (2) the WEC is described using a variable interval, which has strong applicability and operability; and (3) the simulation system can quickly adapt to the changing needs of practical applications and provide managers with visual and credible decision support. The research results provide a theoretical basis for river water environment pollution prevention and environmental management decision-making and help in the high-quality development of the river basin. Full article

Adolescence is a developmental period of significant change and increasing independence, during which parents and caregivers play a critical role guiding their teen toward adulthood. Parents of adolescents with disability face heightened challenges managing their teens’ growing independence and shift to adult-based services across health, recreation, and employment. Using a mixed-methods-treatment-group-only design, this study explored the implementation and outcomes of a program designed to build parenting capacity to support their adolescent with disability. Parents enrolled in one of ten groups were invited to attend three sessions covering content tailored to adolescent development including post-school opportunities, financial support, risk-taking and decision-making, future planning, relationships, and mental health. Surveys were administered pre-program, post-program, and six months after program participation (n = 160) to measure intervention outcomes including parenting self-efficacy, self-advocacy, adolescent self-advocacy, parent confidence to support their adolescent’s growing independence, confidence to support their adolescent through sensitive developmental stages, parental hopes and aspirations, and parental empowerment. A subset of parents (n = 11) also participated in semi-structured interviews about the program’s acceptability and usefulness, and their satisfaction with the program content and delivery. All outcome variables except parent hopes and aspirations increased significantly from pre- to post-program. Parent self-efficacy, self-advocacy, and parental empowerment remained higher 6 months after program completion. Thematic analysis identified program strengths as the co-facilitation model of program delivery, practical and actionable content, the use of narratives and the facilitator’s lived experience as parents of adolescents with disability, the use of visualizations (video, pictures, diagrams), and the service provider’s trusted reputation and credibility. In conclusion, an online co-facilitated group program for parents of adolescents with disability can contribute to positive change for families by improving parent confidence, self-advocacy, and parental empowerment. Full article

William H. Whyte took on the challenge of assessing the amount of public space in a city based on its carrying capacity, pointing out that popular public spaces offer more room for social activities. However, the absence of qualitative characteristics makes this assessment even more challenging to implement. This study aims to find a method to gauge the carrying capacity of urban public spaces by calculating the social space ratio for pedestrian-only streets in Karlstad, Sweden, and quantifying this relationship. The social space ratio represents the proportion of public spaces that foster social interaction throughout their entire area. The method began by selecting the most relevant conceptual framework for social public spaces and then sought theory-based characteristics to assign to seven social activities on Karlstad’s pedestrian-only streets. The authors performed a comprehensive search of the literature utilizing the PRISMA approach, gathering information from credible references, placemaking toolkits, transportation toolkits, and academic sources. This was performed to determine the weighting factors and effective social areas by evaluating these activities in terms of nine categories of the chosen framework: accessibility, traffic, social infrastructure, security, places to meet, senses and experience, architecture and aesthetics, development and maintenance, and control and programming. We devised a method to calculate the carrying capacity and social space ratio of Karlstad’s pedestrian-only streets, resulting in a ratio of 0.38. The research led to the development of eight quality-control tools to analyze the seven social activities in public places. This innovative approach helps researchers and municipal planners evaluate the benefits and drawbacks of these spaces, contributing significantly to Swedish urban planning and enabling future studies to create a social area factor. Full article

This study introduces a novel multi-criteria group evaluation approach grounded in the theory of basic uncertain information (BUI) to facilitate the selection of green recycling suppliers for shared electric bikes. Firstly, a comprehensive index system of green recycling suppliers is established, encompassing recycling capacity, environmental sustainability, financial strength, maintenance capabilities, and policy support, to provide a solid foundation for the scientific selection process. Secondly, the basic uncertain information generalized power weighted average (BUIGPWA) operator is proposed to aggregate group evaluation information with BUI pairs, and some related properties are investigated. Furthermore, the basic uncertain information-based best–middle–worst TOPSIS (BUI-BMW-TOPSIS) model incorporating the best, middle, and worst reference points to enhance decision-making accuracy is proposed. Ultimately, by integrating the BUIGPWA operator for group information aggregation with the BUI-BMW-TOPSIS model to handle multi-criteria decision information, a novel multi-criteria group decision-making (MCGDM) method is constructed to evaluate green recycling suppliers for shared electric bikes. Case analyses and comparative analyses demonstrate that compared with the BUIWA operator, the BUIGPWA operator yields more reliable results because of its consideration of the degree of support among decision-makers. Furthermore, in contrast to the traditional TOPSIS method, the BUI-BMW-TOPSIS model incorporates the credibility of information provided by decision-makers, leading to more trustworthy outcomes. Notably, variations in attribute weights significantly impact the decision-making results. In summary, our methods excel in handling uncertain information and complex multi-criteria group decisions, boosting scientific rigor and reliability, and supporting optimization and sustainability of shared electric bike green recycling suppliers. Full article

An experimental study of cold-formed thin-walled steel unequal-leg angles (CFTWS-ULAs) under axially oriented pressure is presented in this paper. Firstly, the initial imperfections and material properties of the angle specimens were measured in detail. The angle specimens were tested under fixed-ended conditions. The results of the experiments showed that the angle specimens with small slenderness ratios were susceptible to local buckling, the angle specimens whose legs had high slenderness ratios and low width–thickness ratios were found to easily suffer from the occurrence of flexural buckling, and the angle specimens whose legs had high width–thickness ratios were found to easily suffer from the occurrence of interactive buckling between local buckling and flexural buckling. The finite element analysis of the ULAs was conducted using ABAQUS6.14 finite element software by creating a model. The buckling modes and ultimate bearing capacities of the test specimens were compared, and the finite element analysis verified that the established model built using the finite element is credible and subsequent parametric analysis was performed. The slenderness ratio had the most significant impact on the ultimate bearing capacities of the unequal-leg angles, as indicated by the analysis results. When the width–thickness ratio and the width ratio of the legs fell within a specific range, the ultimate bearing capacities of the unequal-leg angles increased as the width–thickness ratio and the width ratio of the legs increased. Finally, the comparison results showed that the design strengths predicted by the specifications were very conservative, because the local buckling and torsional buckling were calculated at the same time. Therefore, a recommendation was proposed that the calculation of the load-carrying capacity of an unequal-leg angle should ignore torsional buckling. Full article

This applied research proposes a solution to the static government design process for Thai healthcare architecture to better serve the needs of its elderly society. In its place, a novel real-time design process, termed the Digital Twin Immersive Design Process (DT-IDP), repurposes aspects of digital twin and virtual reality technologies into a ‘unitary’ immersive design system. This system accesses ‘experiential’ user-centered data, helping enhance the design of Thai healthcare space beyond a standardized government response. This text builds a rationale for departing from the current design process by describing the formation and advantages of the DT-IDP process. To test its credibility, the DT-IDP process is used to build and compare two digital versions of an existing healthcare space. In these spaces, participants are immersed (elderly patients n = 30; nursing staff n = 5; government healthcare architects n = 5) to assess visitor experiences based on daylighting, artificial lighting, and views of nature. Following immersion, government healthcare architects are interviewed in-depth to evaluate the process’s efficacy and their willingness to adopt it. Results confirm the potential for this process to capture ‘user-centered’ insights, otherwise unobtainable without immersion. Consequently, healthcare architects express a unanimous preference for DT-IDP, acknowledging its unique capacity to bridge a market gap through an experiential component that could better assist them in creating a superior final product. Ultimately, they assert that demand for these features could have a disruptive impact to the current healthcare design process, helping to re-envisage the design of future Thai healthcare space. Full article

With the development of unconventional natural gas resources, plunger gas lift technology has gained widespread application. Accurately predicting gas production from unconventional gas reservoirs is a crucial step in evaluating the effectiveness of plunger gas lift technology and optimizing its design. However, most existing prediction methods are mechanism-driven, incorporating numerous assumptions and simplifications that make it challenging to fully capture the complex physical processes involved in plunger gas lift technology, ultimately leading to significant errors in capacity prediction. Furthermore, engineering design factors and production system factors associated with plunger gas lift technology can contribute to substantial deviations in gas production forecasts. This study employs three powerful regression algorithms, XGBoost, Random Forest, and SVR, to predict gas production in plunger gas lift wells. This method comprehensively leverages various types of data, including collected engineering design, production system, and production data, directly extracting the underlying patterns within the data through machine learning algorithms to establish a prediction model for gas production in plunger gas lift wells. Among these, the XGBoost algorithm stands out due to its robustness and numerous advantages, such as high accuracy, ability to effectively handle outliers, and reduced risk of overfitting. The results indicate that the XGBoost algorithm exhibits impressive performance, achieving an R² (coefficient of determination) value of 0.87 for six-fold cross-validation and 0.85 for the test set. Furthermore, to address the “black box” problem (the inability to know the internal working structure and workings of the model and to directly understand the decision-making process), which is commonly associated with conventional machine learning models, the SHAP (Shapley additive explanations) method was utilized to globally and locally interpret the established machine learning model, analyze the main factors (such as starting time of wells, gas–liquid ratio, catcher well inclination angle, etc.) influencing gas production, and enhance the credibility and transparency of the model. Taking plunger gas lift wells in southwest China as an example, the effectiveness and practicality of this method are demonstrated, providing reliable data support for shale gas production prediction, and offering valuable guidance for actual on-site production. Full article

This paper reviews renewable energy integration with the electrical power grid through the use of advanced solutions at the device and system level, using smart operation with better utilisation of design margins and power flow optimisation with machine learning. This paper first highlights the significance of credible temperature measurements for devices with advanced power flow management, particularly the use of advanced fibre optic sensing technology. The potential to expand renewable energy generation capacity, particularly of existing wind farms, by exploiting thermal design margins is then explored. Dynamic and adaptive optimal power flow models are subsequently reviewed for optimisation of resource utilisation and minimisation of operational risks. This paper suggests that system-level automation of these processes could improve power capacity exploitation and network stability economically and environmentally. Further research is needed to achieve these goals. Full article

This article highlights the challenges of rigorously evaluating and meaningfully communicating the socio-economic impacts of arts and crafts in northern Jordan. This article aims to identify and analyse the challenges confronting place-based arts and crafts industries in Jordan and propose valid policies and practices to address these challenges. The methodology employed involved a comprehensive review of the existing literature to elucidate the challenges faced by heritage-based artisans, and we propose several policies aimed at promoting and safeguarding the arts and crafts heritage. The findings supporting this research were derived from a series of practical workshops and focus group interviews conducted in 2022. This article also presents empirical evidence to highlight the identified challenges. It emphasises the importance of the proposed policy recommendations for the Jordanian sector, providing the audience with a sense of empowerment and an understanding of the potential solutions. This work could offer insights into how local communities innovatively leverage creative capacities, create localised impact, and address local challenges. We argue that the value of arts and crafts is better understood locally to provide impactful experiences based on community-led and community-generated creativity and flexibility. A creative participatory approach is used to create contemporary art designs and train young people on artistic and craft-making skills, application, and production as a credible precedent and best practice for developing creative cultural “enterprises” in Jordan. Full article

Ultra-high-performance concrete (UHPC) is widely used in precast concrete-steel composite beams because of its beneficial properties, including reduced structural weight, higher flexural rigidity, and reduced tensile crack formation. In comparison to conventional steel-concrete composite beams, steel-UHPC composite beams exhibit superior characteristics, including reduced structural deadweight, enhanced flexural stiffness, and the capacity to withstand tensile cracking. One successful attempt at meeting the current demands for expedited girder engineering is the development of steel-UHPC composite beams with full-depth precast slabs as key components affecting the overall structural performance using dismountable single embedded nut bolts (SENBs) and widely used studs as competitive alternatives. In contrast, shear connectors are exposed to a combined tensile and shear stress in service life rather than shear only. The corresponding scientific problem is the problem of combined effects under stress in practical applications, but there is currently no relevant research. The shear performance of SENBs in precast steel-UHPC composite beams under tension and shear loads remains unclear. For this purpose, ten push-out specimens and theoretical analyses were performed in this paper, considering the influence of the connector’s type and tensile-to-shear ratio. However, ten specimens were conducted to investigate the tensile-to-shear ratio, and the connector’s type on shear performance is limited. In the future, an increasing number of specimens and test parameters should be considered to investigate the shear performance of precast steel-UHPC composite beams. An increase in the tension-to-shear ratio resulted in a substantial reduction in the ultimate shear capacity, initial shear stiffness, and ductility of the studs. The increase in the tensile-shear ratio from 0 to 0.47 resulted in a 16.9% decline in the ultimate shear capacity, a 30.4% reduction in the initial shear stiffness, and a 21.7% decrease in the ductility of the Series I samples. However, an increase in the tensile-to-shear ratio of the Series II samples from 0 to 0.47 resulted in a 31.3% decline in ultimate shear strength, a 33.2% decline in initial shear stiffness, and a 41.9% decline in ductility. The SENBs demonstrated minimal deviations in ultimate shear capacity compared to their stud counterparts, despite exhibiting notable differences in shear stiffness, and ductility. A lower tensile-to-shear ratio was recommended in practical engineering, which might achieve a larger ultimate shear capacity, stiffness, and ductility. The design-oriented models with enhanced applicability were developed to predict the tension-shear relationship and the load-slip curve of SENBs in prefabricated steel-UHPC composite beams subjected to combined tensile and shear loads. For a tensile-shear relationship model, the point error range was 0 to 0.08, with an average error of 0.03. The square coefficient (R²) was 0.99 for a load-slip curve model. The study findings could offer a credible reference for the shear mechanism of such economical and environmentally friendly precast steel-UHPC composite beams in accelerated bridge construction. Full article

This research highlights the critical role that entrepreneurial capital (EC) plays in organizational development and resilience by examining the connections between EC and the success of new joint ventures (NJVs) in developing nations. Corporate social responsibility (CSR) is becoming more popular in the early phases of a company’s growth because of its capacity to improve credibility and competitive differentiation. Traditionally associated with well-established corporations. This study uses a mediated-moderation model to explore theories on how EC affects the disruptive innovation, economic, social, legal, and environmental sustainability of NJVs. Using quantitative survey data from 270 NJVs, this paper highlights the strategic interdependencies influencing NJV trajectories, as well as the functions of disruptive innovation and CSR. The findings demonstrate that EC greatly enhances NJVs performance in every category, promoting CSR and innovative projects. NJVs benefit from early CSR participation because it reduces risks and boosts entrepreneurial vitality. Disruptive innovation transforms EC into measurable performance advantages. This study has important policy and management implications because it shows that NJVs can stay ahead of the competition and improve their performance by strategically using EC for CSR and innovation projects. Overall, this study emphasizes how crucial CSR is to the startup environment, supporting resilient and long-term growth in emerging economies. Full article

Heat capacity data of many crystalline solids can be described in a physically sound manner by Debye–Einstein integrals in the temperature range from 0K to 300K. The parameters of the Debye–Einstein approach are either obtained by a Markov chain Monte Carlo (MCMC) global optimization method or by a Levenberg–Marquardt (LM) local optimization routine. In the case of the MCMC approach the model parameters and the coefficients of a function describing the residuals of the measurement points are simultaneously optimized. Thereby, the Bayesian credible interval for the heat capacity function is obtained. Although both regression tools (LM and MCMC) are completely different approaches, not only the values of the Debye–Einstein parameters, but also their standard errors appear to be similar. The calculated model parameters and their associated standard errors are then used to derive the enthalpy, entropy and Gibbs energy as functions of temperature. By direct insertion of the MCMC parameters of all 4·105 computer runs the distributions of the integral quantities enthalpy, entropy and Gibbs energy are determined. Full article

Numerical models can be powerful tools for evaluating the best scenarios for the construction of artificial nourishments to mitigate coastal erosion. Until recent decades, when looking at medium- to long-term simulations, cross-shore and alongshore processes have been studied separately. Accounting for both processes in a shoreline evolution numerical model would improve the understanding and predictive capacity of future changes in coastline evolution. The AX-COAST project aims to develop new capacities in modeling cross-shore sediment transport processes by adding the CS-Model, a cross-shore numerical model, into the existing LTC (Long-Term Configuration) model. The LTC model is a shoreline evolution numerical model which is a module of the cost–benefit assessment tool COAST. This work presents the first steps of the CS-Model implementation, which involve evaluating its performance by calibrating the model with extensive measured datasets of wave climate, beach profiles, tide levels, etc., from coastal areas in IJmuiden and Sand Motor in the Netherlands. The results show good agreement between modeled and observed values. Additionally, wave climate datasets derived from global and regional wave models were considered to evaluate modeling performance at IJmuiden. Using derived timeseries from the wave models did not significantly lead to different results compared to using measured data. The obtained mean absolute and relative errors for each profile were low for both types of datasets. Calibration processes with consistent data are important in modeling simulations to accurately represent the study area and ensure the credibility of future simulations. Full article

This study models a container routing problem using multimodal transportation to improve its economy, timeliness, and reliability. Pickup and delivery time windows are simultaneously formulated in optimization to provide the shipper and the receiver with time-efficient services, in which early pickup and delayed delivery can be avoided, and nonlinear storage periods at the origin and the destination can be minimized. Furthermore, the capacity uncertainty of the multimodal network is incorporated into the advanced routing to enhance its reliability in practical transportation. The LR triangular fuzzy number is adopted to model the capacity uncertainty, in which its spread ratio is defined to measure the uncertainty level of the fuzzy capacity. Due to the nonlinearity introduced by the time windows and the fuzziness from the network capacity, this study establishes a fuzzy nonlinear optimization model for optimization problem. A chance-constrained linear reformulation equivalent to the proposed model is then generated based on the credibility measure, which makes the global optimum solution attainable by using Lingo software. A numerical case verification demonstrates that the proposed model can effectively solve the problem. The case analysis points out that the formulation of pickup and delivery time windows can improve the timeliness of the entire transportation process and help to achieve on-time transportation. Furthermore, improving the confidence level and the uncertainty level increases the total costs of the optimal route. Therefore, the shipper and the receiver must prepare more transportation budget to improve reliability and address the increasing uncertainty level. Further analysis draws some insights to help the shipper, receiver, and multimodal transport operator to organize a reliable and cost-efficient multimodal transportation under capacity uncertainty through confidence level balance and transportation service and transfer service selection. Full article