Simulation System Research Articles

Knowledge graph-based representation and recommendation for surrogate modeling method

Surrogate models have been widely used in engineering design for approximating a simulation system with high computational cost. Complex system design typically is a multi-stage and multi-discipline design problem, which requires a large number of surrogate models. The choice of surrogate modeling method (SMM) is critical as it directly impacts the performance of both the surrogate models and the designed systems. With the growing variety of SMMs, designers face challenges in selecting the appropriate methods for their specific applications. To address this, we propose a representation and recommendation framework for surrogate modeling methods based on knowledge graph. Firstly, we develop an ontology to formally represent core concepts involved in the recommendation for surrogate modeling methods, including surrogate modeling method, surrogate model, and data sets,etc. Secondly, we extract 460 samples from 46 benchmark functions using Latin hypercube sampling to construct a knowledge graph with 8,343 nodes and 16,100 relationships, which involves 7,820 surrogate models generated from 17 surrogate modeling methods. Finally, we propose a knowledge graph-based recommendation method for surrogate modeling method named KGRSMM to facilitate the selection of an appropriate surrogate modeling method. We test the efficacy of KGRSMM using examples of theoretical problems and engineering problems of hot rod rolling respectively. It is shown in the results that KGRSMM is capable of recommending surrogates with appropriate accuracy, robustness, and time to satisfy designers’ preferences.

Implementation of a Cuckoo Search intelligent simulation system for node placement problem in Wireless Mesh Networks: Performance evaluation for tuning hyperparameters [formula omitted] and [formula omitted]

In recent years, Internet of Things (IoT) is the hottest topics in the research and implementation of wireless networks. Most of the research of IoT-based applications is related with the data collecting and processing using sensors and actuators. As the network environment for connecting IoT devices are considered WLAN or Bluetooth. The Wireless Mesh Networks (WMNs) are the most suitable networks for the Internet of Things (IoT) due to their numerous benefits. However, they have several issues related to wireless communications. One solution is the optimization of position and location of mesh routers. But finding the best location of mesh routers is an NP-hard problem. To deal with this issue, we propose and implement an intelligent simulation system based on the Cuckoo Search (CS) algorithm called WMN-CS. In the implemented system, the hyperparameters should be tuned to find better solutions. This paper evaluates the WMN-CS performance for various combination of hyperparameters by tuning host bird discovery rate (pa) and scale parameter (γ). The simulation results show that a better performance is achieved when the scale parameter (γ) is between 0.07 and 0.09 and the host bird recognition rate (pa) is between 0.900 and 0.925.

Parameter identification of photovoltaic current loop parameters based on parameter separation

Abstract Accurate control parameters are the basis for analyzing the fault characteristics of PV, but due to technical confidentiality reasons, equipment manufacturers do not provide accurate parameters, so they need to be identified. This paper aims to solve the problem of poor accuracy of the integration coefficient identification of a current loop with low sensitivity by proposing a parameter identification method for a photovoltaic current loop based on parameter separation. By analyzing the current response of the fault and fault recovery stages, the scale coefficient kp and the integration coefficient ki are separated and identified separately. Finally, a simulation system was built on the PSCAD/EMTDC platform, and the validity of the method was verified by using the simulation data.

Ship accident re-enactment based on AIS data and virtual reality: a case study of “Xiang Xiang Yin Huo 0410” ship accident

Abstract The recurrence of ship accidents was an effective method of maritime investigation. To analyze the cause of the sinking of “Xiang Xiang Yin Huo 0410”, a vessel accident recurrence simulation system was constructed by integrating an automatic identification system and virtual reality technology to replicate the navigation and accident process of the accident vessel. The voyaging process of the accident vessel was reduplicated in the simulation system according to the AIS information, such as speed, course, and turning speed. The mathematical model of accident vessel maneuvering was established by using MMG to reproduce the ship maneuvering scheme based on the maneuvering data before the accident obtained through on-the-spot investigation. The navigation and sinking process of the accident vessel were reproduced visually, and the cause of the accident was judged and analyzed intuitively by constructing a three-dimensional model of the accident vessel and a mathematical model of ocean waves. The actual application indicates that the ship’s navigation and accident process under external force, combined with the ship’s maneuvering data, automatic identification data, and hydrometeorological data, was consistent with the actual accident process of the accident. The method proposed in this paper provided a new idea for the investigation and analysis of maritime accidents.

The bactericidal effect of punicalagin concentrations, high pressure conditions and their combination on Escherichia coli O157: H7

Punicalagin (PUN), as a natural antimicrobial agent, is the most abundant phenolic compound in pomegranate peel. In this study, the bactericidal effect of PUN concentrations, high pressure conditions and their combination on E. coli O157: H7 were investigated. The bacteria were suspended in physiological saline solution with PUN concentrations of 1–3 mg/mL and treated by high pressures of 100–300 MPa for 2–10 min. The synergistic effect of the combination treatment was demonstrated with the maximum enhancement value of 4.10. Cell morphology changes, membrane permeability enhancement and swimming motility inhibition were observed in the combination treatment. Adenosine, adenine, cyclic GMP in purine metabolism and glutathione in glutathione metabolism pathways were differential metabolites with content changes, which were related with treatment methods (HPP or PUN) but not the degree of bacteria inactivation. This study provided a more effective and innovative method for killing E. coli in simulation system. Industrial relevanceHPP was the most commercialized emerging non-thermal processing technology and PUN was the natural antibacterial agent from pomegranate peel waste. The combination of HPP and PUN had synergistic bactericidal effect on E. coli with less processing intensity, which was very suitable for the products those contained thermosensitive components with maximum sensory characteristics preserved and less preservative added.

Development of a noninvasive olfactory stimulation fMRI system in marmosets

Olfactory dysfunction is associated with aging and the earliest stages of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases; it is thought to be an early biomarker of cognitive decline. In marmosets, a small non-human primate model used in brain research, olfactory pathway activity during olfactory stimulation has not been well studied because of the difficulty in clearly switching olfactory stimuli inside a narrow MRI. Here, we developed an olfactory-stimulated fMRI system using a small-aperture MRI machine. The olfactory presentation system consisted of two tubes, one for supply and one for suction of olfactory stimulants and a balloon valve. A balloon valve installed in the air supply tube controlled the presentation of the olfactory stimulant, which enabled sharp olfactory stimulation within MRI, such as 30 s of stimulation repeated five times at five-minute intervals. The olfactory stimulation system was validated in vivo and in a simulated system. fMRI analysis showed a rapid increase in signal values within 30 s of olfactory stimulation in eight regions related to the sense of smell. As these regions include those associated with Alzheimer’s and Parkinson’s diseases, olfactory stimulation fMRI may be useful in clarifying the relationship between olfactory dysfunction and dementia in non-human primates.

Research on digital twin architecture of ship maneuverability simulation for system model

Abstract With the development of civil and military requirements, ship maneuverability simulation systems tend to be complicated, and the traditional simulation methods are difficult to meet in terms of the development needs of digitalization. The joint simulation technology based on the FMI standard can realize the digital twin of complex system models, which can solve the difficult problem of multidisciplinary and multi-sub-system integration simulation. This paper analyzes the current domestic and foreign research content on joint simulation technology, digital twin technology, and complex system modeling, takes a typical Z-type maneuverability test as an example, establishes a multidisciplinary and cross-platform subsystem model, and designs and develops a ship maneuverability joint simulation algorithm and system software for the complex system model. The simulation results verify the effectiveness of the system modeling technique and the joint simulation technique based on FMI. Based on this system, the whole framework of the ship maneuverability simulation system, which is based on digital twins, is designed. According to the development requirements of ship maneuverability simulation, the main design framework, key technology, and implementation approach of this research method are given, which provides basic methods and ideas for the digital research of ship maneuverability simulation.

Evolution mechanism of microbial community structure and metabolic activity in aquatic nutrient-poor sedimentary environments driven by 17β-estradiol pollution.

17β-Estradiol (E2) is a novel micro-pollutant that is widely distributed in aquatic sediments and has a universal toxicological effect on aquatic organisms. However, its ecological impact on aquatic microorganisms is not yet clear. In this study, we designed a simulation system for oligotrophic water deposition in the laboratory, analyzed the impact of different concentrations of E2 pollution on the carbon metabolism activity (carbon gas emission rate) of water microorganisms. Based on high-throughput sequencing results, we revealed the impact of E2 pollution on the community structure succession and metabolic function of bacteria, archaea, and methanogens in the simulated system, explored the impact mechanism of E2 pollution on microbial carbon metabolism in water bodies. Our results suggested that E2 significantly impacts the bacterial and archaeal community rather than the methanogen community, thereby indirectly inhibiting methane production. The achievements will bridge the theoretical gap between estrogen metabolism and carbon metabolism in sedimentary environments and contribute to enriching the ecological toxicology theory of steroid estrogen.

Screening of a readily selenium-enriched Spirulina polysaccharide and characterization of its structure and bioactivity

The potential of selenium-containing polysaccharides as organic selenium nutritional supplements has attracted considerable interest; however, they also encounter obstacles, including the presence of impurities and a low selenium binding efficiency. In this study, a novel method combining Q-Sepharose Fast-Flow (QFF) column chromatography with the HNO3–Na2SeO3 method was proposed. Through the application of this methodology, the selenium binding efficiency of polysaccharides was enhanced by a factor of 3.41. The selenium binding capacities of rhamnose and glucose were the highest among the monosaccharides, reaching 770.7 mg/L and 955.3 mg/L, respectively. Spirulina polysaccharide-3 (SPS-3) was selected for further investigation because of its elevated total rhamnose and glucose contents and optimal selenium binding efficiency. Employing common assays, a comparative analysis of selenium-containing Spirulina polysaccharide-3 (SeCSPS) and SPS-3 is presented. Upon selenium binding, the surface morphology of the monosaccharides changed, whereas the main chain structure remained unaltered. The antihyperglycemic activity of SeCSPS was enhanced by selenium binding. Furthermore, both SeCSPS and SPS-3 can be degraded by the simulated digestive system. In conclusion, SeCSPS can be employed as an organic selenium supplement in food or nutraceuticals while also resulting in a high selenium content. The findings of this study will provide a viable avenue for the high-value utilization of Spirulina, which will help resolve the selenium deficiency issue faced by populations with low selenium intake globally.

The Impact of Information Relevancy and Interactivity on Intensivists' Trust in a Machine Learning-Based Bacteremia Prediction System: Simulation Study.

The exponential growth in computing power and the increasing digitization of information have substantially advanced the machine learning (ML) research field. However, ML algorithms are often considered "black boxes," and this fosters distrust. In medical domains, in which mistakes can result in fatal outcomes, practitioners may be especially reluctant to trust ML algorithms. The aim of this study is to explore the effect of user-interface design features on intensivists' trust in an ML-based clinical decision support system. A total of 47 physicians from critical care specialties were presented with 3 patient cases of bacteremia in the setting of an ML-based simulation system. Three conditions of the simulation were tested according to combinations of information relevancy and interactivity. Participants' trust in the system was assessed by their agreement with the system's prediction and a postexperiment questionnaire. Linear regression models were applied to measure the effects. Participants' agreement with the system's prediction did not differ according to the experimental conditions. However, in the postexperiment questionnaire, higher information relevancy ratings and interactivity ratings were associated with higher perceived trust in the system (P<.001 for both). The explicit visual presentation of the features of the ML algorithm on the user interface resulted in lower trust among the participants (P=.05). Information relevancy and interactivity features should be considered in the design of the user interface of ML-based clinical decision support systems to enhance intensivists' trust. This study sheds light on the connection between information relevancy, interactivity, and trust in human-ML interaction, specifically in the intensive care unit environment.

Research on virtual inertia of energy storage systems under different grid-forming control strategies

Abstract To reasonably evaluate the support capability of grid-forming energy storage in power systems characterized by “double high” characteristics, it is essential to investigate the factors influencing the virtual inertia of grid-forming energy storage. This paper delves into the relationship between two control strategies of grid-forming energy storage and virtual inertia from an energy perspective. Initially, the operational principle and technological advantages of grid-forming energy storage are analyzed. Subsequently, based on the principles of two grid-forming control strategies, mathematical models for both types of grid-forming energy storage are established, elucidating the physical significance of virtual inertia in grid-forming inverters and revealing the adjustability of virtual inertia. Finally, a microgrid simulation system is constructed in PSCAD to validate the theoretical analysis.

Correcting Optical Aberration via Depth-Aware Point Spread Functions.

Optical aberration is a ubiquitous degeneration in realistic lens-based imaging systems. Optical aberrations are caused by the differences in the optical path length when light travels through different regions of the camera lens with different incident angles. The blur and chromatic aberrations manifest significant discrepancies when the optical system changes. This work designs a transferable and effective image simulation system of simple lenses via multi-wavelength, depth-aware, spatially-variant four-dimensional point spread functions (4D-PSFs) estimation by changing a small amount of lens-dependent parameters. The image simulation system can alleviate the overhead of dataset collecting and exploiting the principle of computational imaging for effective optical aberration correction. With the guidance of domain knowledge about the image formation model provided by the 4D-PSFs, we establish a multi-scale optical aberration correction network for degraded image reconstruction, which consists of a scene depth estimation branch and an image restoration branch. Specifically, we propose to predict adaptive filters with the depth-aware PSFs and carry out dynamic convolutions, which facilitate the model's generalization in various scenes. We also employ convolution and self-attention mechanisms for global and local feature extraction and realize a spatially-variant restoration. The multi-scale feature extraction complements the features across different scales and provides fine details and contextual features. Extensive experiments demonstrate that our proposed algorithm performs favorably against state-of-the-art restoration methods.

Validation of a surgical simulator and establishment of quantitative performance thresholds—RealSpine simulation system for open lumbar decompressions

BACKGROUND CONTEXTThe majority of surgical training is conducted in real-world operations. High-fidelity surgical simulators may provide a safer environment for surgical training. However, the extent that it reflects real-world operations and surgical ability is often poorly characterized. PURPOSE(1) Assess the validity and fidelity of a surgical simulator; (2) Examine the quantitative relationship between simulation performance and markers of real-world ability; (3) Establish thresholds for surgical expertise, and estimate their external validity and accuracy. STUDY DESIGN/SETTINGA cohort study of surgeons at a British neurosurgical center. STUDY SAMPLETen early-career “novice” surgeons and 8 board-certified “expert” neurosurgeons. OUTCOMES MEASURES(1) Face and content validity, and visual and haptic fidelity; (2) Construct validity; (3) Predictive and discriminative utility of quantitative performance thresholds. METHODSParticipants performed unilateral lumbar decompressions on high-fidelity spinal simulators that replicate the bony and soft tissue anatomy along with physiological processes such as bleeding and CSF leaks. Operating times, measured from first surgical action to either self-perceived satisfactory decompression or the end of allocated time, were recorded. The performance was also assessed independently by 2 blinded spinal subspecialist neurosurgeons using OSATS, a validated surgical assessment tool that utilizes 5-point scales on a variety of technical domains to grade the overall technical proficiency. Validity and fidelity were assessed by expert neurosurgeons using quantitative questionnaires. Construct validity was assessed by ordinal regression of simulation performance against real-world surgical grade and portfolio. Thresholds of expert status by simulation performance was established, and their predictive and discriminative utility assessed by crossvalidation accuracy and AUC-ROC. RESULTSOperating time and expert assessments of simulation performance (OSATS) were strong and significant prdictors of surrogate markers of real-world surgical ability. The thresholds for expert status were operating time of 15 minutes and modified OSATS score of 15/20. These thresholds predicted expert status with 84.2% and 71.4% accuracy respectively. Strong discriminative ability was demonstrated by AUC-ROC of 0.95 and 0.83 respectively. All expert surgeons agreed that RealSpine simulators demonstrate high face validity, and high visual and haptic fidelity, with overall scores showing statistically significant agreement on these items (all scores at least 4/5, p<.0001). There was less consensus on content validity, but with still significant overall agreement (average score: 3.75/5, p=.023). CONCLUSIONSReal-world surgical ability and experience can be accurately predicted by defining objective quantitative thresholds on high-fidelity simulations. The thresholds established here, along with other data presented in this paper, may inform objectives and standards to be established in a spinal surgical training curriculum.

The satellite galaxy plane of NGC 4490 in light of ΛCDM

Context. The system of galaxies around NGC 4490 was recently highlighted to display a flattened, kinematically correlated structure reminiscent of planes of satellite galaxies around other hosts. Aims. Since known satellite planes are in tension with expectations from cosmological simulations in the Λ cold dark matter (ΛCDM) model, we aim to quantitatively assess for the first time the tension posed by the NGC 4490 system. Methods. We measured the on-sky flattening as the major-to-minor axis ratio b/a of the satellite distribution and their line-of-sight kinematic correlation. Analogs to the system were selected in the TNG50 simulation and their flattening and correlation were similarly measured. Results. We confirm the strong kinematic coherence of all 12 observed satellite objects with available line-of-sight velocities (of 14 in total): the northern ones approach and the southern ones recede relative to the host. The spatial distribution of all 14 objects is substantially flattened with b/a = 0.38 (0.26 considering only the 12 objects with available velocities). Such extreme arrangements are rare in the ΛCDM simulation, at a level of 0.21 to 0.35%. This fraction of analogs would drop further if at least one of the two satellite objects without velocities is confirmed to follow the kinematic trend, and would become zero if both are rejected as non-members. We also identify a likely galaxy pair in the observed system, and find a similar pair in the best-matching simulated analog. Conclusions. Our measurements establish NGC 4490 as another strong example of a satellite plane in the Local Volume. This emphasizes that planes of satellites are a more general issue faced by ΛCDM also beyond the Local Group. The tension with typical systems drawn from simulations suggests that the observed one requires a specific formation scenario, potentially connected to the larger-scale galaxy alignment in its vicinity. The presence of galaxy pairs in the observed and a simulated system hints at the importance such groupings may have to understand satellite planes.

Multi-fracture growth behavior during TPDF in a horizontal well of multi-clustered perforations: An experimental research

Temporary plugging and diverting fracturing (TPDF), involving inner-fracture temporary plugging (IFTP) and inner-stage temporary plugging (ISTP), has been proposed as a widely applied technique in China, for promoting the uniform initiation and propagation of multi-clustered hydraulic fractures (HFs) in a horizontal well of the shale oil/gas reservoirs. However, how the key plugging parameters controlling the multi-fracture growth and the pumping pressure response during TPDF in shale with dense bedding planes (BPs) and natural fractures (NFs) is still unclear, which limits the optimization of TPDF scheme. In this paper, a series of TPDF simulation experiments within a stage of multi-cluster in a horizontal well were carried out on outcrops of Longmaxi Formation shale using a large-scale true tri-axial fracturing simulation system, combined with the acoustic emission (AE) monitor and computed tomography (CT) scanning techniques. Each experiment was divided into three stages, including the conventional fracturing (CF), IFTP and ISTP. Multi-fracture initiation and propagation behavior, and the dominant controlling parameters were examined, containing the particle sizes, concentration of temporary plugging agent (TPA), and cluster number. The results showed that the number of transverse HFs (THFs) and the overall complexity of fracture morphology increase with the increase in TPA concentration and perforation cluster number. Obviously, the required concentration of TPA is positively correlated with the cluster number. Higher peak values and continuous fluctuations of pumping pressure during TPDF may indicate the creation of diversion fractures. The creation of standard THFs during CF is favorable to the creation of diversion fractures during TPDF. Moreover, the activation of BPs nearby the wellbore during CF is unfavorable to the subsequent pressure buildup during TPDF, resulting in poor plugging and diverting effect. Notably, under the strike-slip fault stress regime, the diversion of THFs is not likely during IFTP, which is similar as the results of ISTP to initiate mainly the un-initiated or under-propagated perforation clusters. Three typical pressure curve types during TPDF can be summarized to briefly identify the hydraulic fracture diversion effects, including good (multiple branches or/and THFs can be newly created), fair (HF initiation along the slightly opened BPs and then activating the NFs), and bad (HF initiation along the largely opened BPs and then connecting with the NFs).

Experimental analysis of ice crystal size–velocity correlation in icing wind tunnel with digital holographic particle tracking velocimetry

The ice crystal icing in aero-engines poses a significant threat to aircraft flight safety, and investigating the correlation between ice crystal size and velocity in icing wind tunnels is essential for correlating ground tests with flight conditions. In this paper, a digital holographic particle tracking velocimetry system is developed and integrated with an icing wind tunnel, and the ice crystal size and velocity are simultaneously measured in experiments at four different wind speeds. The velocity difference between the ice crystal and wind has been experimentally observed, and it increases with both the ice crystal size and wind speed. The normalized velocities of the ice crystals by the wind speeds decrease with size, and the maximum velocity difference in the experiments reaches 28% of the wind speed. Additionally, quantitative correlations between ice crystal size and normalized velocity based on the power function and polynomial model are established. The relationship between the particle Reynolds number of ice crystal and size is also analyzed, resulting in the development of a model based on the power function, and the power index ranges from 1.51 to 1.64. These findings will provide valuable assistance in the calibration and commissioning of the ice crystal simulation system in icing wind tunnels, as well as in exploring the correlation between ground icing tests and flight and in developing corresponding models.

Consistency and repeatability verification for vehicle in the loop test platform based on digital twin of proving ground

Abstract A high-confidence vehicle-in-the-loop test method based on the digital twin of proving ground (DTPG-VIL) is proposed for the test of autonomous driving vehicles. The overall architectural design of the DTPG-VIL and the corresponding components are introduced, with a focus on describing the scene simulation system based on the digital twin of the proving ground. A King Long intelligent driving sightseeing bus for test verification is introduced, and its positioning performance is verified by the high-definition positioning base station and GPS/INS combined navigation system to verify the accuracy of its positioning precision and meet the requirements of the digital twin test so that the DTPG-VIL can obtain more information from the bus. Taking the automatic emergency avoidance function as an example, the method, process, and experimental results of the control test between the DTPG-VIL test and the real vehicle test in a proving ground are designed. Through the correlation coefficient analysis and transient response analysis, consistency and repeatability comparisons are carried out to verify the high confidence of the digital twin test.

Giant planet formation in the Solar System

The formation history of Jupiter has been of interest due to its ability to shape the solar system’s history. Yet little attention has been paid to the formation and growth of Saturn and the other giant planets. Here we explore through N-body simulations the implications of the simplest disc and pebble accretion model with steady-state accretion and an assumed ring structure in the disc at 5 AU on the formation of the giant planets in the solar system. We conducted a statistical survey of different disc parameters and initial conditions of the protoplanetary disc to establish which combination best reproduces the present outer solar system. We examined the effect of the initial planetesimal disc mass, the number of planetesimals and their size-frequency distribution slope, pebble accretion prescription and sticking efficiency on the likelihood of forming gas giants and their orbital distribution. The results reveal that the accretion sticking efficiency is the most sensitive parameter to control the final masses and number of giant planets. We have been unable to replicate the formation of all three types of giant planets in the solar system in a single simulation. The probability distribution of the final location of the giant planets is approximately constant in logr, suggesting there is a slight preference for formation closer to the Sun but no preference for more massive planets to form closer. The eccentricity distribution has a higher mean for more massive planets indicating that systems with more massive planets are more violent. We compute the average formation time for proto-Jupiter to reach 10 Earth masses to be 〈tc,J〉=1.1±0.3 Myr and for proto-Saturn 〈tc,S〉=3.3±0.4 Myr, while for the ice giants this increases to 〈tc,I〉=4.9±0.1 Myr. The formation timescales of the cores of the gas giants are distinct at >95% confidence, suggesting that they formed sequentially.

Design of the distribution of iron oxide (Fe3O4) nano-particle drug in realistic cholangiocarcinoma model and the simulation of temperature increase during magnetic induction hyperthermia

The prognosis for Cholangiocarcinoma (CCA) is unfavorable, necessitating the development of new therapeutic approach such as magnetic hyperthermia therapy (MHT) which is induced by magnetic nano-particle (MNPs) drug to bridge the treatment gap. Given the deep location of CCA within the abdominal cavity and proximity to vital organs, accurately predict the individualized treatment effects and safety brought by the distribution of MNPs in tumor will be crucial for the advancement of MHT in CCA. The Mimics software was used in this study to conduct three-dimensional reconstruction of abdominal computed tomography (CT) and magnetic reso-nance imaging images from clinical patients, resulting in the generation of a realistic digital geometric model representing the human biliary tract and its adjacent structures. Subsequently, The COMSOL Multiphysics software was utilized for modeling CCA and calculating the heat transfer law resulting from the multi-regional distribution of MNPs in CCA. The temperature within the central region of irregular CCA measured approximately 46°C, and most areas within the tumor displayed temperatures surpassing 41°C. The temperature of the inner edge of CCA is only 39 ∼ 41℃, however, it can be ameliorated by adjusting the local drug concentration through simulation system. For CCA with diverse morphologies and anatomical locations, the multi-regional distribution patterns of intratumoral MNPs and a slight overlap of drug distribution areas synergistically enhance intratumoral temperature while ensuring treatment safety. The present study highlights the practicality and imperative of incorporating personalized intratumoral MNPs distribution strategy into clinical practice for MHT, which can be achieved through the development of an integrated simulation system which incorporates medical image data and numerical calculations.

Evaluation of the coupling of EMACv2.55 to the land surface and vegetation model JSBACHv4

Abstract. We present the coupling of the Jena Scheme for Biosphere–Atmosphere Coupling in Hamburg version 4 (JSBACHv4) to the ECHAM/MESSy Atmospheric Chemistry (EMAC) model. With JSBACH, the soil water bucket model in EMAC is replaced by a diffusive hydrological transport model for soil water that includes water storage and infiltration in five soil layers, preventing soil from drying too rapidly and reducing biases in soil temperature and moisture. A three-layer soil scheme is implemented, and phase changes in water in the soil are considered. The leaf area index (LAI) climatology in EMAC has been substituted with a phenology module calculating the LAI. Multiple land cover types are included to provide a state-dependent surface albedo, which accounts for the absorption of solar radiation by vegetation. Plant net primary productivity, leaf area index and surface roughness are calculated according to the plant functional types. This paper provides a detailed evaluation of the new coupled model based on observations and reanalysis data, including ERA5/ERA5-Land datasets, Global Precipitation Climatology Project (GPCP) data and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. Land surface temperature (LST), terrestrial water storage (TWS), surface albedo (α), net top-of-atmosphere radiation flux (RadTOA), precipitation (precip), leaf area index (LAI), fraction of absorbed photosynthetic active radiation (FAPAR) and gross primary productivity (GPP) are evaluated in particular. The strongest correlation (r) between reanalysis data and the newly coupled model is found for LST (r=0.985, with an average global bias of −1.546 K), α (r=0.947, with an average global bias of −0.015) and RadTOA (r=0.907, with an average global bias of 3.56 W m−2). Precipitation exhibits a correlation with the GPCP dataset of 0.523 and an average global bias of 0.042 mm d−1. The LAI optimisation yields a correlation of 0.637 with observations and a global mean deviation of −0.212. FAPAR and GPP exemplify two of the many additional variables made available through JSBACH in EMAC. FAPAR and observations show a correlation of 0.663, with an average global difference of −0.223, while the correlation for GPP and observations is 0.564 and the average global difference is −0.001 kg carbon km−1. Benefiting from the numerous added features within the simulated land system, the representation of soil moisture is improved, which is critical for vegetation modelling. This improvement can be attributed to a general increase in soil moisture and water storage in deeper soil layers and a closer alignment of simulated TWS with observations, mitigating the previously widespread problem of soil drought. We show that the numerous newly added components strongly improve the land surface, e.g. soil moisture, TWS and LAI, while surface parameters, such as LST, surface albedo or RadTOA, which were mostly prescribed according to climatologies, remain similar. The coupling of JSBACH brings EMAC a step closer towards a holistic comprehensive Earth system model and extends its versatility.