Actual Situation Research Articles

Assessment of Rural Industry Integration Development, Spatiotemporal Evolution Characteristics, and Regional Disparities in Ethnic Regions: A Case Study of Inner Mongolia Autonomous Region Counties

Ethnic regions in China primarily focus on the development of agricultural and animal husbandry economies, which are relatively underdeveloped. Rural industry integration development (RIID) is considered the foundation and guarantee for ethnic regions to achieve high-quality modernization of agriculture. The purpose of this article is to measure the level of rural industrial integration in ethnic minority areas, analyze the spatial evolution and regional differences, and explore the actual situation of RIID in these regions. The aim is to provide a decision-making basis for local governments to effectively promote the development of rural industrial integration. Based on the improvement of the evaluation index system for rural industrial integration development, this paper takes the counties of the Inner Mongolia Autonomous Region as the research area. Utilizing panel data from the statistical yearbooks of 68 banners and counties in Inner Mongolia from 2011 to 2020, the panel entropy weight TOPSIS method is employed to assess the average level of rural industrial integration in the research area. The ArcGIS natural breakpoint method is employed to classify the level of RIID in county areas. Exploratory Spatial Data Analysis (ESDA) and GeoDa are utilized to analyze the spatial distribution characteristics of RIID. Finally, the Theil index is employed to analyze the regional differences in the level of RIID. The results show the following: (1) The overall level of RIID in ethnic regions is relatively low, with the contributions of the four dimensions in the evaluation index system as follows: integration path > integration foundation > integration sustainability > integration effect. The level of RIID in the study area is as follows: western region > eastern region > central region. (2) Spatially, there are positive correlations and significant spatial clustering in the level of RIID, with the spatial clustering effect of RIID weakening. (3) There are regional differences in the level of RIID, which are expanding. The inter-regional differences are decreasing, while the intra-regional differences are increasing. (4) The construction of agricultural processing facilities, financial investment, financial support, and talent policies are important influencing factors for the current stage of RIID in ethnic regions. Therefore, in the low-level development stage of RIID in ethnic regions, it is necessary to fully utilize the advantages of resource endowment, increase investment in rural infrastructure, and strengthen the guidance of talent flow into rural revitalization construction.

Research Progress on Numerical Simulation of the Deposition and Deformation Behavior of Cold Spray Particles

It is of significant theoretical and practical value to study the deposition process and deformation behavior of cold-sprayed particles to find the deposition mechanism of cold-sprayed coatings, further improve the coating performance, and expand its application scope. However, observing the deposition process and particle behavior through experiments is difficult due to the brief deposition duration of cold spray particles. Numerical simulation offers a means to slow the deposition process and predict the critical velocity, deformation behavior, bonding mechanism, and residual stress of cold-sprayed particles. This paper uses finite element analysis software, including ANSYS LS Dynamic-2022 R1 and ABAQUS-6.14, alongside various prevalent finite element methods for numerically simulating cold spray particle deposition. These methods involve the Lagrange, Euler, arbitrary Lagrange-Euler (ALE), and Smoothed Particle Hydrodynamics (SPH) to investigate the cold spray particle deposition process. The recent literature primarily summarizes the simulation outcomes achieved by applying these methodologies for simulating the deposition process and deformation characteristics of different particles under varying cold spraying conditions. In addition, the reliability of these simulation results is analyzed by comparing the consistency between the simulation results of single-particle and multi-particle and the actual experimental results. On this basis, these methods’ advantages, disadvantages, and applicability are comprehensively analyzed, and the future simulation research work of particle deposition process and deformation behavior of cold spraying prospects is discussed. Future research is expected to provide a more in-depth study of the micro-mechanisms, such as the evolution of the inter-particle and internal organization of the particles, near the actual situation.

Grasp the Momentum: Define and Prediction Models for Accurate Trend

In tennis, the concept of momentum is used to describe the reversal of a player's big lead. However, motivation in sports is subjective and difficult to quantify. To address this challenge, the study aims to build models that can predict momentum and successful streaks. We accomplished three main tasks. Task one involves assessing player motivation using a variety of metrics and analytic hierarchy process (AHP). Task two includes proving strong autocorrelation and testing fringes using run tests. The results show significant autocorrelation, which is suitable for momentum regression prediction. In Mission three, the random forest method is used to calculate the importance of features to provide suggestions for the player's next game. The long short-term memory (LSTM) model is used to predict the trend of the next game and the momentum of the players, showing good reliability and accuracy. The sensitivity analysis and robustness verification show that it is consistent with the actual situation and the error range is acceptable. Finally, the advantages and disadvantages of the model are summarized, and suggestions for further improvement are put forward.

Study of the Dynamic Reaction Mechanism of the Cable-Stayed Tube Bridge under Earthquake Action

In order to explore the failure mode of the cable-stayed pipe bridge under earthquake action, taking the structural system of an oil and gas pipeline–cable-stayed pipe bridge as the research object, the full-scale finite element calculation model of the cable-stayed pipe bridge–oil and gas pipeline structural system as well as the finite element calculation model considering the additional mass of the oil and gas medium and the fluid–structure interaction effect were established by using ANSYS Workbench finite element software. The stress and displacement of the cable under the earthquake action were analyzed in the time history, as were the response characteristics of the cable when subjected to both methods. The calculation results show that the overall failure of the pipeline is basically the same under the two methods. Compared with the additional mass method, the solution for the fluid–structure coupling method can be derived through a comprehensive analysis of the flow field and structure, respectively, avoiding the sudden change caused by model simplification or calculation error so that the analysis results can better simulate the actual situation. In summary, the fluid–structure interaction method enables a more precise prediction of the dynamic response of the structure, and the findings of this research can provide a theoretical foundation and technical guidance for optimizing the seismic performance of cable-stayed pipe bridges.

Construction and Innovation of Management Mode of Laboratory in Regional and Local Universities

University laboratory is an important base for training students' innovative practice ability and teachers' scientific and technological innovation, and is an important part of university. Traditional laboratory management methods have been unable to adapt to modern practical teaching and scientific and technological innovation. Based on the comprehensive analysis of laboratory management in local colleges and universities and the actual situation of existing laboratories, a comprehensive laboratory management system was developed, which consisted of six functional modules: large-scale equipment sharing platform, instrument and equipment maintenance system, experimental consumables management system, laboratory and practice teaching integrated service platform and laboratory safety management and service platform. The system fully integrates and displays the laboratory teaching resources, realizes the open self-management mode, provides the convenience of experimental teaching, and effectively improves the efficiency and management level of the laboratory.

Multi-scenario analysis and optimization strategy of ecological security pattern in the Weihe river basin

For many years, the Weihe River Basin (WRB) has struggled to achieve a balance between ecological protection and economic growth. Constructing an Ecological Security Pattern (ESP) is extremely important for ensuring ecological security (ES). This study employed a coupling of multi-objective programming (MOP) and the patch-generating land use simulation (PLUS) model to project land use change (LUCC) in 2040 across three scenarios. Leveraging circuit theory, we generated ecological corridors and identified key ecological nodes, enabling a comparative analysis of ESPs within the WRB. The main results showed that: (1) The Ecological Protection (EP) scenario showed the highest proportions of forestland, grassland, and water, indicating an optimal ecological environment. Conversely, the Economic Development (ED) scenario features the greatest proportion of construction land, particularly evident in the rapid urban expansion. The Natural Development (ND) scenario exhibits a more balanced change, aligning closely with historical trends. (2) The ecological source areas in the EP scenario is 13,856.70 km2, with the largest and most intact patch area. The ecological source patches that have been identified in the ED scenario exhibit fragmentation and dispersion, encompassing a total area of 8018.82 km2. The ecological source areas in the ND scenario is most similar to the actual situation in 2020, encompassing 8474.99 km2. (3) The EP scenario demonstrates minimal landscape fragmentation. The ED scenario presents a more intricate corridor pattern, hindering species and energy flow efficiency. The ND scenario is more similar to the actual distribution in 2020. Protecting and restoring key ecological nodes, and ensuring the integrity and connectivity of ecological sources are crucial for ESP optimization in various scenarios. Combining all results, we categorize the WRB's spatial pattern into "three zones, three belts, and one center" and offer strategic suggestions for ecological preservation, promoting sustainable local ecological and socioeconomic development.

Study on updating finite element model of steel truss structure based on knowledge-enhanced deep reinforcement learning

Accurate assessment of the damage to a structure is the key to structural health monitoring. Among them, one effective means to assess the real-time status of the structure is by establishing a finite element model (FEM) of the structure and updating it synchronously. Previous research mainly updates the FEM of the structure with a certain moment in time without considering the continuous changes of structural parameters over a longer time. In this paper, we propose a FEM updating method for steel truss structure based on knowledge-enhanced deep reinforcement learning, which introduces long short-term memory (LSTM) network based on a deep deterministic policy gradient (DDPG) algorithm and constructs a knowledge-enhanced noise function (NF) module based on parametric analysis. The NF-LSTM-DDPG algorithm can fit a continuous variation of structural parameters. The ablation experiments revealed that the LSTM network and the NF module facilitate the exploration and learning ability of the DDPG algorithm. The NF-LSTM-DDPG algorithm is used in an actual steel truss structure case, and the variation rules of the elastic modulus and support deviations obtained from the solution are consistent with the actual situation. The average relative error of the 34 strain measurement points after updating is 14.147 %, and the relative error is higher than 20 % in only 13 days out of 187 days of continuous monitoring. Five days were selected for the comparative study, and the experimental results show that the relative error of the NF-LSTM-DDPG algorithm is 13.206 %, which is higher than that of the particle swarm optimization algorithm and the simulated annealing algorithm. The change of elastic modulus updated based on the NF-LSTM-DDPG algorithm is more reasonable than other algorithms.

Experimental study of jet and cavity coupling under vertical motion of underwater vehicle

After the underwater vehicle detaches from the launch tube and starts its engine, the interaction between the tail cavity and the high-speed jet significantly impacts its motion stability and engine efficiency. Therefore, it is crucial to study the evolution mechanism of cavities in vertical motion. However, in traditional water tunnel experiments, the evolution of the cavity differs from the actual situation of vertical launch due to the influence of buoyancy. This study investigates the dynamics and motion trajectories of tail cavities and high-speed gas jets in the vertical movement of vehicles under different Froude numbers and nozzle stagnation pressure ratios through experimentation. The experimental results show two modes of tail cavity evolution: intact cavity (IC) and foam-conical cavity (FC-CC). Increasing the Froude numbers and stagnation pressure ratios facilitates the transition of the cavity from the IC mode to the FC-CC mode, effectively suppressing the formation and intensity of re-entrant jets, thereby reducing its impact on the bottom of the vehicle and enhancing motion stability. By deriving the formula for the length of the jet core area, it was found that the jet length is linearly related to the nozzle stagnation pressure, further revealing the mechanism of cavity evolution. These findings offer a new perspective for a deeper understanding and prediction of the dynamic behavior of underwater vehicles.

The impact of different business models on the environmental and economic benefits of public charging facilities

ABSTRACT This paper explores the impact of different charging pile business models on their economic and environmental benefits. Firstly, this paper analyzes the cooperation and competition relationships among the stakeholders under three charging pile business models, and their impact on the whole process of charging pile from design, production, operation to recycling. Secondly, this paper establishes a social economic benefit evaluation model and a life cycle carbon emission evaluation model based on the differences of charging pile in quality, cost, life span and high-value component recycling rate under different business models. Finally, this paper conducts a case analysis of the economic and environmental benefits of three business models combined with China’s actual situation. The research results show that the economic and environmental benefits of each party in the three business models are closely related to the quality, cost, life span and high-value component recycling rate of the charging pile. Among them, the life span of the charging pile has the greatest impact on its economic and environmental benefits. The higher the recycling rate of high-value components, the more conducive to improving its economic and environmental benefits. The research results will provide reference for policy makers and EVCI investors.

Research on the Protection System for Smart Grid Based on Phasor Information at Circuit Breakers

A smart grid protection system based on phasor information at circuit breakers is proposed in this paper. Phasor data for fault diagnosis is obtained from phasor measurement units or intelligent electronic devices installed near circuit breakers, without the need for additional measurement equipment. When a fault occurs, the protection system first locates the core protection circuit breaker closest to the fault point. It then identifies the faulty component by analyzing the current phasor differences between this breaker and adjacent ones. This scheme offers high computational efficiency, enabling rapid identification of faulty equipment and its precise location. The proposed protection system structure can be divided into two types: centralized and decentralized, and the most suitable scheme should be selected based on the actual situation. Finally, the feasibility of the proposed scheme was verified through the IEEE 39-bus system and a simulated actual area power grid model, demonstrating its applicability to practical smart grid scenarios. The simulation network validates the implementation method of the proposed protection strategy.

Ethical requirements of instructions for authors of complementary and alternative medicine journals: a cross-sectional study

BackgroundMedical research in complementary and alternative medicine (CAM) has increased recently, raising ethical concerns about the moral status of CAM. Medical academic journals are responsible for conducting ethical review (ER) of manuscripts to protect the interests of human subjects and to make ethical results available before deciding to publish. However, there has been no systematic analysis of the ER in CAM journals. This study is aim to evaluate the current status of ethical requirements and compliance in CAM journals.MethodsThis is a cross-sectional study. We reviewed instructions for authors (IFAs) of CAM journals included in the Journal Citation Reports (2021) (https://jcr.clarivate.com) for general information and requirements for ER. We also browsed the manuscripts regarding randomized controlled trials published by CAM journals in Q1 and Q2 section from January to June, 2023, to check the actual situation of ethical requirement. Descriptive statistics and Fisher’s exact test were used for statistical analysis.Results27 journals and 68 manuscripts were ultimately included. 92.6% (25/27) IFAs included keywords of ER, indicating the presence of ethical considerations. However, no specific ER was required for CAM (n = 0). We categorized journals by Geographic origin, JCR section, Year of electronic JCR, Types of studies, % of OA Gold to explore the factors that could influence CAM journals to have certain ethical review policies. The results showed there was no statistical significance in certain ethical review policy in any classification of journals (p > 0.05). All RCT manuscripts included in the study generally met the requirements of the published journals for ethical review.ConclusionsAll IFAs discussed ER, but the content was scattered, unfocused, and there were no specific ER requirements regarding CAM. Although the manuscripts basically met the requirements of the journal, it was not possible to get closer to the process of ER in the manuscript. To ensure full implementation of these policies in the future, CAM journals should require authors to provide more details, or to form a list of items necessary for CAM ethical review.

ANALISIS KINERJA KEUANGAN BERDASARKAN RASIO PROFITABILITAS DAN RASIO LIKUIDITAS PADA PT. PANCA USAHA MAKMUR

The purpose of this research is to find out the financial performance of the PT. Panca Usaha Makmur in the years 2019–2021. The types of data used in the research are primary data and secondary data. This research uses a descriptive approach, i.e., a method performed by collecting, classifying, analyzing, and interpreting data related to the problem encountered and comparing the secondary information obtained with the actual situation in the company to draw conclusions. Based on the data analysis, the financial performance through the profitability ratio and the liquidity ratio at the P.T. Panca Usaha Makmur is very poor, where the value of each ratio is below the average. Return on assets in 2019 was 0.01%, in 2020 it was 0.046%, and in 2021 it was 0.036%. Return on equity in 2019 at 3.40%, in 2020 at 9.57%, and in 2021 at 5.88%. The current ratio in 2019 is 0.58%; in 2020, it is 0.51%; in 2021, it is 0.80%. Cash ratio was 0.49% in 2019, 0.35% in 2020, and 0.55% in 2021. This makes the company need to make improvements as well as improvements for the sustainability of good financial performance of the company.

On the characterization of EM emission of electronic products: Case study for different program modes

The characterization of the EM emissions for electronic products is crucial to ensure that the emissions have met the requirements of the EMC standards. For this, a more comprehensive testing is required to get more meaningful results. While, the emergence of non-stationary emissions is a challenge to obtain valid analysis results. So far, non-stationary EM emissions is not considered and treated properly in the emission analysis. This paper presents a new method for the analysis of EM emissions from electronic devices as a case study by testing three different program modes (scenarios) of Intel Galileo board. These program modes were designed to vary processing intensity in its memory and processor. A comparison was also made between the actual situation (the presence of non-stationary signals) and the hypothetical situation with the assumption that all emissions were stationary. As a result, a significant difference was observed when the analysis considered the real scenario of a non-stationary emission. The ratio between the average autocorrelation using the proposed algorithm and the average correlation by ignoring the non-stationarity of the emission signal was 113.6 times. The study concludes that different program modes produce the different characteristics of EM emissions, making some of them non-stationary. Hence, we strongly suggest the consideration of the non-stationarity of the EM emissions in characterizing complex electronic devices.

A new two-stage emergency material distribution framework for urban rainstorm and flood disasters to promote the SDGs

Under the coupled effects of climate change and urbanization, urban rainstorm and flood has become more frequent and intense. The effect of the flood disasters emergency response has a direct impact on the success or failure of the rescue. Emergency material distribution is one of the most critical steps in the emergency response phase and is crucial to achieve the Sustainable Development Goals (SDGs). This study proposes a two-stage emergency material distribution framework for urban rainstorm and flood disasters. The entropy weight method and technique for order preference by similarity to ideal solution (EWM-TOPSIS) was adopted to incorporate the difference in relief-demand urgency into the emergency material distribution principle. The mathematical model was established by minimizing emergency travel time, inequity and social costs (logistic costs and deprivation costs) as objective functions. The gamultiobj algorithm was used to solve the model. The proposed framework is further applied in Xi'an city of China. The results showed that the affected sites were categorized into disaster risk levels I, II and III. The Pareto solution set was obtained by optimizing each conflicting objective. The emergency material distribution plan was selected from the Pareto solution set based on the actual situation. In the plan, the flood disasters emergency travel time totaled 6.48 h, the inequity totaled 3.69, and the total social costs reached 226,584 CNY. The proposed framework is more consistent with the needs of the actual rescue by comparing the four models generated plans. Decision-makers should not only consider minimizing dispatch time and social costs, but also the trade-off between equity and prioritization of distribution. This study helps to provide new ideas for sustainable urban development and emergency management. Urban rainstorm and flood disasters change with the changing environment dynamically, and it is difficult to collect dynamic disaster information on the affected sites. Thus our further study will focus on improving the prediction accuracy of dynamic urban rainstorm and flood disasters.

The Impact of Pedestrian Lane Formation by Obstacles on Fire Evacuation Efficiency in the Presence of Unfair Competition

After a fire breaks out, pedestrians simultaneously move towards the exit and quickly form a crowded area near the exit. With the intensification of pedestrians’ tendencies towards unfair competition, there is an increase in pushing and collisions within the crowd. The possibility of stampedes within the crowd also gradually increases. Analyzing the causes and psychological tendencies behind pedestrian pushing and collisions has a positive effect on reducing crowd instability and improving evacuation efficiency. This research proposes a modified social force model considering the unfair competition tendency of pedestrians. The model considers factors such as the gap between pedestrians’ actual and maximum achievable speed, effective radius, and their distance from the exit. In order to overcome the shortage of “deadlock” in the classical social force model in a high-density environment, this research introduces the feature of variable pedestrian effective radius. The effective radius of pedestrians dynamically changes according to the density of the surrounding crowd and queuing time. Through validation, the evacuation efficiency of this model aligns well with the actual situation and effectively reflects pedestrians’ pushing and squeezing behaviors in high-density environments. This research also analyzes how to strategically arrange obstacles to mitigate the exacerbating effect of unfair pedestrian competition on exit congestion. Five experiments were conducted to analyze how the relative position of obstacles and exits, the number of evacuation paths, and the size of the obstacle-free area before the exit affect evacuation efficiency in the presence of unfair pedestrian competition. The results show that evacuation efficiency can be improved when obstacles play a role in guiding or reducing the interaction of pedestrians in different queues. However, when obstacles hinder pedestrians, the evacuation efficiency is reduced to a certain extent.

Comparison on Environmental Benefits of Municipal Solid Waste Management in Suzhou Before and After Classification

In order to systematically understand the urban environmental benefit improvement of municipal solid waste （MSW） classification, based on the disposal data of MSW before and after the MSW classification in Suzhou from 2017 to 2021, the environmental impact potential （EIP） of the MSW collection-transportation-disposal process was calculated, and the environmental benefits of the MSW integrated management in Suzhou to 2035 were predicted. After the MSW classification in Suzhou at the end of 2019, the EIP （in terms of PET2000, the same below） of the per unit weight of MSW was reduced by 18.38% from 2.34×10-13 t-1 in 2017 to 1.91×10-13 t-1 in 2021. The environmental benefits of the MSW integrated management could be improved by classification. Based on the Suzhou MSW removal and transportation situation in 2021, different classification and disposal scenarios were established to calculate. It was found that after the classification effect showed gradient improvement, and the disposal capacity matched accordingly, the environmental benefits of MSW were further improved. Under the planning disposal capacity scenario of "zero waste to landfill", the EIP and the total carbon emissions of per unit weight of MSW should be reduced by 23.96% and 30.73%, respectively, compared with the actual situation in 2021. Based on the linear model of population and economic development level of Suzhou, it is expected that the annual production of MSW in Suzhou will be increased to 6.965 million tons in 2035. Under the background of continuous improvement of MSW classification and continuous optimization of city appearance and environment in Suzhou, based on the status quo of terminal disposal capacity in Suzhou, the EIP of per unit weight of MSW after improving the efficiency of classification by 2035 was predicted to be 1.54×10-13 t-1, the total EIP would be 1.05×10-6, and the total carbon emissions would increase to 3.80 million tons. Under the ideal scenario of expanding the scale of waste disposal, "zero landfill" of raw MSW, and full resource utilization of food waste, the EIP of per unit weight of MSW in 2035 was predicted to be 1.28×10-13 t-1, and the total EIP and the total carbon emissions would be 8.69×10-7 and 3.23 million tons, respectively, which was approximately 5.65% and 1.23% less than the actual scenario in 2021, respectively. The EIP and carbon emissions of MSW integrated management could be controlled better by the coordinated promotion of classified collection and transportation and quality disposal.

Accuracy Analysis of Complex Transmission System with Distributed Tooth Profile Errors

Tooth profile errors are the internal excitations that cause gear meshing errors, which are critical error factors affecting gear transmission accuracy. In existing studies, it is usually regarded as a constant or random distribution function. However, the actual machined tooth profile error is not a constant, so this estimation is inconsistent with the actual situation, resulting in an inaccurate evaluation of transmission accuracy. This paper proposes a method for representing tooth profile errors using distribution errors (including systematic and random errors), and a mathematical model of distributed tooth profile errors is presented. The contact stresses of the complex transmission system were compared with those obtained by formulas, proving that tooth profile errors increase contact stress. A method for calculating gear meshing error is proposed to evaluate the actual output accuracy of the complex transmission system. Compared with the test, the output accuracy is reduced by 13.8% under the temperature environment and distributed tooth profile errors. The proposed methods can accurately predict the transmission accuracy of precision transmission systems at the design stage and provide theoretical support for reducing systematic and random errors at the gear machining stage.

Delivering Goods Sustainably: A Fuzzy Nonlinear Multi-Objective Programming Approach for E-Commerce Logistics in Taiwan

With the booming development of e-commerce, the importance of controlling carbon emissions has become increasingly prominent in Taiwan. This study explores the trade-offs among time, cost, quality, and carbon emissions (TCQCE) in e-commerce logistics. Will carbon emissions mitigation lead to decreased logistics efficiency and increased costs? This article differs from other studies that use precise numbers and linear model situations. This study adopts fuzzy theory, nonlinear methods, and multi-objective programming models closer to the actual situation to study the decision-making between delayed logistics delivery times and reduced carbon emissions. This article also uses Project D as a case to enhance readers’ understanding of decision-making methods in real-life e-commerce logistics cases. The results show that extended delivery times could significantly reduce carbon emissions, ranging from 5259.31 to 419,199.60 tons, and reduce delivery quality under the 90.00% threshold and even under 75.25%. Extending delivery times is a viable business strategy, particularly by extending delivery to push carbon reduction policies to minimize environmental impact. However, consumer acceptance is crucial, as consumers willing to embrace longer wait times can significantly contribute to emission mitigation and support businesses committed to sustainability. This research uses a fuzzy nonlinear multi-objective programming model (FNMOPM) to contribute novel time management to mitigate carbon emissions. Moreover, this study uses a fuzzy and nonlinear approach to fill in the gaps of previous research to balance the efficiency and carbon emission mitigation goals of ESG (environmental, social, and governance) principles. The framework presented in this article solves the complex trade-off situations in the TCQCE issues. This article provides practical, actionable guidance for decision-making regarding sustainable e-commerce logistics, instilling confidence in its implementation.

A Method of Integrating Air Conditioning Usage Models to Building Simulations for Predicting Residential Cooling Energy Consumption

Great deviations in building energy consumption simulation are attributed to the simplified settings of occupants’ air conditioning (AC) usage schedules. This study was designed to develop a method to quantify the uncertainty and randomness of AC usage behavior and incorporate the model into simulations, in order to improve the prediction performance of AC energy consumption. Based on long-term onsite monitoring of household thermal environments and AC usage patterns, two stochastic models were built using unsupervised cluster and statistical methods. Based on the Monte Carlo method, the AC operation schedule was generated through AC opening duration, setpoints, and other relevant parameters, and was further incorporated into EnergyPlus. The results show that the ideally deterministic AC operation settings from the standard significantly overestimate the cooling energy consumption, where the value based on the fixed mode was 6.35 times higher. The distribution of daily AC energy consumption based on the stochastic modeling was highly consistent with the actual situation, thanks to the accurate prediction of the randomness and dynamics of residents’ AC usage patterns. The total cooling energy consumption based on two stochastic models was found to be much closer to the actual values. The work proposes a method of embedding stochastic AC usage models to EnergyPlus 22.1 benefits for an improvement in building energy consumption simulation and the energy efficiency evaluation regarding occupant behavior in the future.

Effect of airflow rate on droplet deposition of an impinging-jet inhaler in the human respiratory tract

This paper presents a numerical investigation to understand the transport and deposition of sprays emitted by an impinging-jet inhaler in the human respiratory tract under different inhalation flow rates. An injection model is used for the numerical simulations considering the spreading angles of the spray in the two directions, which are measured from experiments. The model parameter is adjusted to match the mean droplet size measured in the previous experiment. A time-varying sinusoidal inhalation flow rate is utilized as airflow conditions, which is closer to the actual situation when using an inhaler. The results demonstrate that the inhalation airflow rate significantly affects the spray’s transport behavior and deposition results in the respiratory tract. Both excessively high and low inhalation flow rates lead to an increase in deposition in the mouth-throat. A moderate inhalation flow rate reduces throat deposition while maximizing lung deposition. Higher inhalation flow rates enable faster delivery of the droplets to the lungs, whereas lower inhalation flow rates achieve a more uniform deposition over time in the lungs. The amount of deposition in different parts of the lung lobes follows a fixed order. This study provides valuable insights for optimizing the inhalation flow rate conditions of the impinging-jet inhaler for clinical applications.