Matching Relationship Research Articles

Spatial risk assessment of maritime transportation in offshore waters of China using machine learning and geospatial big data

Maritime transportation plays a crucial role in global trade and economic development. However, this industry is exposed to various risks (e.g., natural disasters), which can cause significant economic and environmental damage. This study aims to develop a spatial risk assessment approach for maritime transportation using machine learning and geospatial big data to identify potential risks in China's maritime transportation industry. The proposed approach first produces risk maps that reveal significant variability in maritime transportation risks across different regions of China. Then, factor importance analysis identifies wave height, rainfall, and sea surface temperature as the most influential factors affecting navigational safety. Finally, capability indicators are employed to analyze the matching relationship between coastal search and rescue resources and maritime transportation risks. Our study provides valuable references for enhancing maritime emergency response capabilities and protecting marine ecological environments.

Evolution Pattern and Spatial Mismatch of Urban Greenspace and Its Impact Mechanism: Evidence from Parkland of Hunan Province

Planners need to fully understand the quantity of land supply and its matching relationship with population demand, as these are prerequisites for urban greenspace planning. Most papers have focused on single cities and parks, with little attention paid to comparative analysis between multiple cities on a macro scale, ignoring the influence of spatial effects and leading to a lack of basis for regional green infrastructure planning. This paper selected 102 cities in Hunan province as case studies to comprehensively conduct empirical research using the spatial mismatch model and the geographically weighted regression method. The urban parkland in Hunan province are characterized by significant spatial heterogeneity and correlation, and the mismatch between land supply and population demand should not be ignored, with oversupply and undersupply co-existing. The urban parkland and its mismatch with population are influenced by a number of factors, and each factor has a stronger influence on the latter than the former. Different factors vary widely in the nature and intensity of their effects, and the dynamics are more complex. Economic development, financial capacity, and air quality are key factors, with the former having a negative impact and the latter having opposite (positive) effects. We suggest that when the government allocates land resources and targets for urban parks, it should formulate a differentiated allocation plan based on the supply and demand conditions of each city; besides, it should also place emphasis on regional integration and coordination and support mutual cooperation.

Robust coverless video steganography based on inter-frame keypoint matching

Existing coverless video steganography schemes primarily focus on single-frame features, which manifest poor robustness. To enhance resistance against adversarial attacks, this paper proposes a coverless video steganography method based on inter-frame keypoint matching, leveraging the movement orientation of keypoints within the video for information hiding. Initially, the method divides video frames into blocks, and then constructs an inter-frame keypoint matching network by using the keypoint detection method combined with deep learning. By narrowing down the matching scope and filtering out mismatches, the network effectively discerns the keypoint matching relationships. For keypoints successfully matched within the blocks, a coordinate system is established based on the original keypoint, determining the position of the matched keypoints. The most frequently occurring orientation within the blocks is designated as the orientation of the block. Subsequently, we introduce a mapping rule based on quadrant labels, generating robust hash sequences according to the quadrant labels corresponding to the orientation of the blocks. Compared to the latest coverless video steganography schemes, this method shows superior robustness in resisting 14 common traditional attacks and video attacks. Concurrently, it exhibits commendable hiding capacity and hiding success rate.

Research on seismic behavior of CFST column-H-beam fully assembly joint

At present, the studies of the joint of concrete-filled steel tubular (CFST) columns-H-shaped steel beams mainly focus on its traditional cast-in-place construction methods. It lacks studies on the realization of prefabricated CFST column-H-shaped steel beam joint prefabricated assembly connection. The traditional cast-in-place construction method is hard to ensure the pouring quality of concrete and is not conducive to the development of prefabricated buildings in this connection form. Therefore, a joint that realized the full assembly of prefabricated CFST columns-H-shaped steel beams was proposed in this paper, the seismic performance of which was investigated by using low-cycle repeated experiments and simulations. The test indicated that the thickness of the end plate in the core area impacted immensely the failure mode and bearing capacity of the fully assembled joint. However, the energy dissipation capacity and plastic deformation capacity were less affected. Meanwhile, the simulation indicated that the mechanical performance of the core area of the joint can be improved by an appropriate thickness of the steel tubular column. Nevertheless, the excessive local deformation of the end plate caused a decrease in the energy dissipation capacity of the joint. The thin thickness of the end plate caused the end plate at the flange to be subjected to excessive deformation and the core area column not to be fully utilized, resulting in a significant decrease in the bearing capacity and stiffness of the joint. Finally, the initial rotational stiffness calculation model of the assembled joint was established and the stiffness matching relationship between the joint components was determined.

The effects of deployment friction on the dynamics of nonconductive space tethers

At present, the neglect of deployment friction could lead to a significant deviation in the numerical results from the real deployment dynamic characteristics of the nonconductive space tether. To solve this problem, a dedicated experimental setup for tether deployment was firstly employed to measure the deployment friction of nonconductive space tether, the dependences of the deployment friction on the tether diameter, deployment velocity and deployment angle (which is the angle between the deployment direction and the normal direction of the tether exit) were determined. The effect of deployment parameters on the dynamics in both the uncontrolled tether deployment and the station-keeping stages were evaluated based on the “dumbbell” and “extended dumbbell” models, the measured deployment frictions was applied to the models. The numerical results show that the uncontrolled nonconductive tether deployment is great limited by the deployment friction; the tether deployment capability and dynamic stability could be enhanced by increasing the initial deployment velocity (≤2 m/s) and satellite effective mass, as well as decreasing the orbital altitude. To guarantee maximum tether deployment capability and dynamic stability, an optimal matching relationship between the tether full length and satellite total mass is given, which is of substantial importance for the uncontrolled deployment process of the nonconductive space tether system at the design stage.

An investigation on structural parameters optimization and coupled heat transfer of LNG submerged combustion vaporizer

Submerged combustion vaporizer (SCV) owns an extremely efficient multiphase heat exchanger adopted in the coastal liquefied natural gas (LNG) receiving terminal. Overall vaporization efficiency of SCV mostly depends on the matching relationship of structural parameters and coupled heat transfer characteristics, which has been rarely addressed in previous studies. In the present work, an integrated SCV experimental platform with handling capacity of 50 kg/h was set up to validate the reliability of numerical model and method. Additionally, on account of multi-parameter orthogonal combination optimization method, the effects and sensitivity orders of structural parameters (transverse tube pitch, longitudinal tube pitch, orifice size and number of distributor branch) on dynamics performance of SCV were investigated. Finally, the coupled heat transfer between gas–liquid two-phase flow and supercritical LNG gasification was revealed in view of optimized parameters. Results indicated that the transient numerical tube-side outlet temperature could be consistent with experimental data. For the shell-side heat transfer coefficient, the sensitivity order was transverse tube pitch > orifice size > longitudinal tube pitch > number of distributor branch. Nevertheless, for the shell-side pressure drop, the sensitivity order was longitudinal tube pitch > transverse tube pitch > orifice size > number of distributor branch. Under the condition of optimization scheme, the heat provided by gas–liquid two-phase flow could meet the requirements of supercritical LNG gasification, the NG outlet temperature might achieve approximately 272 K. The present outcomes could lay a foundation for the optimization design and deep understanding for actual SCV facility.

Study on the Ecosystem Service Supply–Demand Relationship and Development Strategies in Mountains in Southwest China Based on Different Spatial Scales

Mountainous regions typically exhibit a strained relationship between humans and the land, with noticeable spatial differences in the supply and demand of ecosystem services (ESS and ESD, respectively). ESS and ESD display varying characteristics at different spatial scales. Research on ESS and ESD at multiple scales can aid regional development and efficient ecosystem management. However, the current research focuses on ESS and neglects the ES characteristic changes at different scales. This study concentrates on the Hengduan Mountain region in southwest China. It evaluated ESS and ESD, analyzed the spatial matching relationship, and proposed a corresponding development strategy. The results demonstrated four key findings. First, ESS displayed an inverse spatial distribution on the two scales and was lower in the north and higher in the south at the raster scale. Over the period 2000–2020, ESS exhibited a pattern of initial increase, followed by a decrease, albeit with varying spatial patterns. Changes in land use primarily drove these ESS changes. Second, ESD increased from northwest to southeast on both scales and showed a rising trend over time. Third, at the grid scale, the low supply and low demand (L-L) region is primarily situated in the northwestern part, and it is crucial to prevent grassland degradation and manage grazing intensity. The low supply and high demand (L-H) region is located in the southeast, where the protection of cultivated land, along with comprehensive control of rocky desertification and debris flow, should be prioritized. High supply and low demand (H-L) are found in the northern mountain area, where paying attention to soil erosion control is essential. For areas with high supply and high demand (H-H) types, efforts should be directed toward maintaining forest habitat integrity. Fourth, on the county scale, L-H types should focus on realizing the ecosystem service value and implementing ecological agriculture. H-L counties can appropriately develop economic activities. Simultaneously, ecological compensation should be conducted among counties.

Influence Analysis of Impeller-Guide Vane Matching on Energy and Pressure Pulsation in a Tubular Pump Device

Tubular pump devices offer advantages such as low hydraulic losses, a simple structure, and easy maintenance. They find extensive application in areas such as irrigation, flood control, and water diversion. The performance and security of the pump are directly impacted by the contact between the impeller and guide vane. The matching relationship between the number of impeller blades and guide vanes significantly influences this interaction in tubular pump devices. To explore this impact, a Very-Large-Eddy Simulation turbulence model was employed to simulate the 3D flow fields of six different number matching relationships in a shaft tubular pump device. The analysis focused on the energy performance of the different schemes, the flow distribution of the guide vanes, and the velocity circulation at the guide vanes’ outlet. Entropy theory and energy gradient theory were employed to understand how the number matching relationship influences energy performance. Additionally, pressure pulsations were analyzed at the impeller and guide vanes for different matching configurations. The results indicate that although increasing the number of impeller blades can lead to higher water circulation, increased energy, and potentially unstable water flow, an increase in impeller blades number results in improved flow distribution in each guide vane groove, leading to an overall enhancement in the efficiency of the pump device. Similarly, increasing the number of guide vanes may increase the non-uniformity of the guide vane flow rate, but it also enhances the ability of the guide vanes to regulate water circulation and recover energy, thereby benefiting the overall efficiency.

Self-assembly, structure and catalytic activity of Ni3 on TiO2: A triple-atom catalyst for hydrogen evolution

Triple-atom catalysts (TACs), structurally derived from single-atom catalysts (SACs) but beyond SACs in the active sites, have received increasing attention but are still in their infant stage. Using density functional theory, we study the self-assembly of the Ni3 trimer on TiO2 (Ni3/TiO2) by atom-by-atom deposition. Coordinatively unsaturated sites on the TiO2 surface are responsible for this self-assembly, resulting in different configurations of Ni3. According to the orientation relationship and lattice mismatch, an embryo of Ni crystal is thought to be born of triangle Ni3 trimer on TiO2. The hydrogen evolution reaction activity and mechanism of Ni3/TiO2 with different H coverages are evaluated using thermochemistry and kinetics calculations. Only at high H coverage would Ni3/TiO2 TACs exhibit a hydrogen production activity higher than that of Ni1/TiO2 SACs, indicating the matching relationship between multiple active sites and multi-step reaction intermediates for the active-site utilization. The quantum confinement effect throughout Nin/TiO2 (n = 1–3) is evidenced by the localization of metallic states of Nin. Our results not only open the possibility for synthesizing multimers on oxides by self-assembly, but also enrich the quantum control toolbox in few-atom catalysts by coordination modulation.

Single-Chip Switchable Dual-Wavelength Vertical External-Cavity Surface-Emitting Laser

Dual-wavelength output devices have a wide range of applications in mid-infrared band difference frequency generation, anti-interference lidar, dual-wavelength holographic interferometry, and other applications. Vertical external cavity surface-emitting lasers (VECSELs) are a type of semiconductor laser that can achieve single-chip dual-wavelength output by designing the chip structure. In this paper, we present a single-chip VECSEL that can switch between dual-wavelength and single-wavelength output modes. The VECSEL can simultaneously emit coaxial laser beams at 967 nm and 1013 nm, with a wavelength spacing of about 45 nm. The degree of mismatch between the gain peaks of the two quantum wells in the gain chip and the corresponding cavity modes is different. By adjusting the pump power, the temperature of the active region can be changed, which alters the matching relationship between the gain peaks and the cavity modes and controls the output mode of the VECSEL. The dual-wavelength output mode maintains a stable wavelength spacing at different operating temperatures. The laser output mode can be switched between single-wavelength and dual-wavelength, and the beam divergence angle is less than 8°. The dual-wavelength output power can exceed 400 mW, and the long-wavelength output power can reach up to 700 mW.

Optimization of the matching relationship between the stemming length and minimum burden in cut blasting of large-diameter long-hole stopes

Cut blasting, in which new surfaces and relief space for subsequent blasting are created, is one of the most critical steps in the establishment of large-diameter long-hole (LDL) stopes. To reduce the damage to the chamber roof caused by stemming recoil and improve the rock breaking effect, 15 groups of small-scale model tests with minimum burdens of 3, 4, 5, 6, and 7 cm and stemming lengths of 0, 2, 4, 5, 6, and 7 cm were designed to optimize the matching relationship between the stemming length and minimum burden. First, through the model tests, values were obtained for ten evaluation indexes related to the total mass of fragments, crate size, fragment size, fragmentation energy consumption, and stemming recoil area. Then, the normal cloud combination weighting method was used to combine six subjective and objective weighting methods, and combined weights were obtained. Finally, the test schemes were optimized according to the Euclidean distance and similarity. The test results showed that the best blasting scheme involves a burden of 5 cm and a stemming length of 5 cm, followed by that involving a burden of 4 cm and a stemming length of 4 cm, and the optimal stemming length is approximately equal to the minimum burden. A field test of LDL stope cut blasting was conducted, with a stemming length of 2.2 m and a minimum burden of 2.2 m in the boreholes. The highly satisfactory field blasting effect indicates that the stemming length and minimum burden are reasonable.

CASMatching strategy for automated detection and quantification of carotid artery stenosis based on digital subtraction angiography

Background and objectiveAutomated detection and quantification of carotid artery stenosis is a crucial task in establishing a computer-aided diagnostic system for brain diseases. Digital subtraction angiography (DSA) is known as the "gold standard" for carotid stenosis diagnosis. It is commonly used to identify carotid artery stenosis and measure morphological indices of the stenosis. However, using deep learning to detect stenosis based on DSA images and further quantitatively predicting the morphological indices remain a challenge due the absence of prior work. In this paper, we propose a quantitative method for predicting morphological indices of carotid stenosis. MethodsOur method adopts a two-stage pipeline, first locating regions suitable for predicting morphological indices by object detection model, and then using a regression model to predict indices. A novel Carotid Artery Stenosis Matching (CASMatching) strategy is introduced into the object detection to model the matching relationship between a stenosis and multiple normal vessel segments. The proposed Match-ness branch predicts a Match-ness score for each normal vessel segment to indicate the degree of matching to the stenosis. A novel Direction Distance-IoU (2DIoU) loss based on the Distance-IoU loss is proposed to make the model focused more on the bounding box regression in the direction of vessel extension. After detection, the normal vessel segment with the highest Match-ness score and the stenosis are intercepted from the original image, then fed into a regression model to predict morphological indices and calculate the degree of stenosis. ResultsOur method is trained and evaluated on a dataset collected from three different manufacturers' monoplane X-ray systems. The results show that the proposed components in the object detector substantially improve the detection performance of normal vascular segments. For the prediction of morphological indices, our model achieves Mean Absolute Error of 0.378, 0.221, 4.9 on reference vessel diameter (RVD), minimum lumen diameter (MLD) and stenosis degree. ConclusionsOur method can precisely localize the carotid stenosis and the normal vessel segment suitable for predicting RVD of the stenosis, and further achieve accurate quantification, providing a novel solution for the quantification of carotid artery stenosis.

A Lightweight Visual Odometry Based on LK Optical Flow Tracking

Autonomous mobile robots (AMRs) require SLAM technology for positioning and mapping. Their accuracy and real-time performance are the keys to ensuring that the robot can safely and accurately complete the driving task. The visual SLAM systems based on feature points have high accuracy and robustness but poor real-time performance. A lightweight Visual Odometry (VO) based on Lucas–Kanade (LK) optical flow tracking is proposed. Firstly, a robust key point matching relationship between adjacent images is established by using a uniform motion model and a pyramid-based sparse optical flow tracking algorithm. Then, the grid-based motion statistics algorithm and the random sampling consensus algorithm are used to eliminate the mismatched points in turn. Finally, the proposed algorithm and the ORB-SLAM3 front-end are compared in a dataset to verify the effectiveness of the proposed algorithm. The results show that the proposed algorithm effectively improves the real-time performance of the system while ensuring its accuracy and robustness.

Understanding driving mechanisms behind the supply-demand pattern of ecosystem services for land-use administration: Insights from a spatially explicit analysis

Uncovering the highly complex driving mechanisms behind ecosystem services (ESs) supply-demand matching relationships is of great significance for achieving sustainable eco-environment and land planning. Unfortunately, the effects within this process are still inadequate and spatially explicit knowledge of the surplus-deficit status for multiple ESs remain under-researched. The study area is the Bairin Left Banner, located in North East of China. In detail, a comprehensive framework was proposed to fill this research gap by coupling the assessment of ESs supply-demand, spatial correlations and driving analysis. The results showed that: (1) the surplus for all ESs was dominant in northern mountains covered with forests whereas deficit was observed in southern urban areas. Specifically, the spatially mismatched supply-demand pattern for habitat quality and carbon storage was predominant while that relation for soil conservation and water yield was spatially aligned in general. (2) the relationships between ESs supply and demand were affected by different socio-ecological factors with positive effects from natural drivers while negative influences from social factors on the whole. The supply-demand matching degrees for habitat quality and water yield were more susceptible to slope and population density. Precipitation and vegetation were proved to be dominant factors for controlling surplus of soil conservation while the supply-demand pattern for carbon storage was mainly affected by vegetation and population. (3) The results of multi-scale geographically weighted regression showed its superiority with more accurate estimations compared to traditional methods. Drastic human activities would adversely affect ESs supply-demand matching while abundant precipitation coupled with more vegetation could create favorable conditions for forming surplus ESs status. Based on these new findings, some land planning and eco-environment management measures were suggested to achieve the supply-demand coordination of various ESs in arid regions. The proposed framework could deliver deeper insights into the field of ESs supply-demand analysis and the targeted proposals were also valuable for policymaking worldwide.

Analysis of the effect of user-understanding-based retrieval system improvement on the application of intelligent archive management

Abstract As a precipitation and accumulation of history, archives management has gradually tended to be digitalized and informalized with the continuous updating and development of modern technology. In this paper, we first study the retrieval system and focus on the Boolean model, vector model, and probabilistic model in information retrieval technology. The matching relationship between documents and queries is detected from the document set for the user’s query, and a relevance retrieval system based on user understanding is proposed to solve the matching problem. The amount of information that needs to be retrieved is growing exponentially, and how a user perceives the information is crucial to the process. Then, in order to solve the problem of insufficient retrieval efficiency caused by the explosive growth of wisdom files, the retrieval system is creatively optimized on the basis of the ant colony algorithm, which effectively improves the efficiency of wisdom file management. The efficiency of the optimized retrieval system is verified and analyzed in an experimental simulation environment. The findings demonstrate that when the amount of archives rises, the retrieval effectiveness of the improved ant colony algorithm described in this study marginally improves, but in 10~35s. As the inventory of the Smart Archives increases, the content retrieval of the archives will become more and more frequent. This study improves retrieval efficiency and serves as a good demonstration for the construction of archival management information technology.

Improving the accuracy of stereolithography 3D printed Al2O3 microcomponents by adding photoabsorber: Fundamentals and experiments

Ceramic microcomponents have a wide range of applications in microfluidic, sensors, etc. Stereolithography 3D printing technology provided a shortcut for the preparation of this small-size and complex component. With the development of device miniaturization, the existing stereolithography forms cannot meet the demand. To prepare smaller components, it is necessary to decrease the slice thickness (Cs). But during the stereolithography 3D printing, ceramic is usually easy to over-cure, leading to the key issue in the stereolithography of ceramic microcomponents: the mismatching between the curing thickness (Cp) and the slice thickness (Cs). To solve the problem above, this paper started from the stereolithography mechanism of the ceramic/resin slurry and adjusted the matching relationship between Cp and Cs theoretically by adding a photoabsorber. Then, from the experiments, the influence of different content of photoabsorber (carbon black) on curing thickness, printing accuracy, and sintering accuracy, were studied. Al2O3 ceramic microcomponents that met the design requirements were thus prepared. These results would help in the development of stereolithography 3D printing of ceramic microcomponents.

Reassignment Algorithm of the Ride-Sourcing Market Based on Reinforcement Learning

Reassignment strategies are of great significance to improve the dispatching efficiency of the ride-sourcing market by reassigning drivers and passengers. However, due to the focus on the feasibility of the reassignment strategy in the short period, previous studies ignore possible reassignment opportunities in the future and inevitably make short-sighted reassignment decisions. To fully exploit the effect of the reassignment strategy, this study proposes a two-stage reassignment framework, which integrates a reinforcement learning algorithm and the bilateral matching reassignment model. The Markov decision process is adopted to dynamically model the reassignment problem. In the framework, the reinforcement learning algorithm is utilized to first learn the randomness and dynamics of travel patterns from historical data and select vehicles participating in the reassignment process. Then, the bilateral matching reassignment model formulates the matching relationship after reassignment for passengers (drivers). Furthermore, for the cases where reassignment may increase individual matching distance, a personalized bilateral matching reassignment model is developed to avoid that. Experiments based on real data in Beijing found that learning passenger travel patterns and adjusting vehicle reassignment moments can greatly improve the passenger experience and reduce driving costs. The results also suggest that the efficiency of the reassignment strategy is influenced by the supply and demand conditions of the ride-sourcing system. This justifies that the framework can be applied to optimize the dispatching process, reduce carbon emissions, and build an eco-friendly travel system.

Matching Characteristics of CTHP Circulation Systems

Cogeneration can not only reduce the use of primary energy, but also reduce the pollution to the environment; the article selects a 1200kW low-pressure stage turbine as an example to give an analysis, calculates the variation of parameters such as heat production, heat production coefficient, flow rate of cold water and hot water of this turbine, and proposes and analyzes the circulation characteristics of the CTHP system, determines the matching relationship between the steam engine driven heat pump that the system needs to meet, and fits the relationship between the steam engine efficiency and power of the heat pump. The correlation equation of steam engine efficiency and power is regressed, and the relationship of circulating cooling water flow rate with turbine discharge temperature is fitted. It is found that the heat production performance coefficients of the high and low pressure stages of the heat pump increase by 27.6% and 29.3% respectively when the discharge temperature increases from 160°C to 220°C, and the system can realize better economic and social benefits compared with the conventional CHP system.

To be precise (imprecise) in utilitarian (hedonic) contexts: Examining the influence of numerical precision on consumer reactions to artificial intelligence‐based recommendations

AbstractThe precision of artificial intelligence (AI)‐generated information has been suggested in the past as a method of nudging consumers' evaluations and intentions, but little is known about whether such effects are also context‐sensitive. Based on four studies, we find a matched condition under which consumers are more likely to make a positive response when precise (imprecise) numbers presented by AI recommenders are used in a utilitarian (hedonic) consumption context (Study 1). Additionally, we show that consumer conceptual fluency also mediates this matching effect on consumer purchase decision‐making (Studies 2). We further show the matching effect is moderated by the recommender type (Study 3) and consumer lay beliefs about the AI and human recommenders (Study 4). This study shows that when consumers' lay belief changes from “AI performs objective tasks well” and “Human performs subjective tasks well” to “AI performs subjective tasks well” and “Human performs objective tasks well,” it can change the difference in the matching relationship between human and AI recommenders.

Load characteristics analysis of the water source heat pump heating system using data center waste heat

The number and scale of data centers (DCs) in China are constantly expanding with the advancement of networking and informatization. A large amount of waste heat is dissipated at its end. If this waste heat can be recovered, then achieving carbon neutrality in DCs can be effectively accelerated. At present, water source heat pump (WSHP) are widely used in air-cooled and liquid-cooled DCs of different sizes for waste heat recovery. This study analyzes the equipment type and heating capacity of different brands of WSHP units. Three WSHP heating systems are proposed according to the different locations of waste heat enhancement (SE, TDE, UE). The coupling and matching relationship between user-side heat load demand, DC waste heat load, and energy efficiency of WSHP units under different systems is also investigated. Moreover, the law of energy consumption and energy efficiency changes is analyzed. Thus, this study provides a reference for the DC waste heat recovery system design and equipment development. The results show that the coupling matching relationship between user-side heat load demand, DC waste heat load, and heating COP of WSHP units is Q.N/Q.S=COP′/COP′-1=φ, where φ ranges from 1.1962 to 1.3642. The heating COP of the SE system is the greatest when user-side heat load demand is between 0 and 120 kW. The heating COP of the TDE system is the highest when the user-side heat load demand is between 1750 and 70000 kW. Furthermore, the heating COP of the three WSHP heating system types is related to unit brand when user-side heat load demand is between 120 and 1750 kW.