Modular Model Research Articles

RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface

We present a new Python toolkit called RecWizard for Conversational Recommender Systems (CRS). RecWizard offers support for development of models and interactive user interface, drawing from the best practices of the Huggingface ecosystems. CRS with RecWizard are modular, portable, interactive and Large Language Models (LLMs)-friendly, to streamline the learning process and reduce the additional effort for CRS research. For more comprehensive information about RecWizard, please check our GitHub https://github.com/McAuley-Lab/RecWizard.

Exploring Comprehension Strategies of Modular Process Models: A Combined Eye-Tracking and Concurrent Think-Aloud Study.

The study of complex process models often encounters challenges in terms of comprehensibility. This paper explores using modularization as a strategy to mitigate such challenges, notably the reduction in complexity. Previous research has delved into the comprehensibility of modularized process models, yet an unresolved question about the cognitive factors at play during their comprehension still needs to be answered. Addressing the latter, the paper presents findings from an innovative study combining eye-tracking and concurrent think-aloud techniques involving 25 participants. The study aimed to comprehend how individuals comprehend process models when presented in three different modular formats: flattened process models, models with grouped elements, and models with subprocesses. The results shed light on varying comprehension strategies employed by participants when navigating through these modularized process models. The paper concludes by suggesting avenues for future research guided by these insights.

Dependability model of automated intelligent regenerative life support system for space missions

Long-duration human space missions require intelligent regenerative life support systems that can recycle resources and automatically manage failures. This paper explores using Petri nets to model the reliability and complex interactions of such closed-loop systems. An architecture consisting of primary systems, backups, and consumable reserves is outlined. The automation system that controls everything is described. Petri nets can capture concurrency, failure modes, redundancy, and dynamic behavior. A modular modeling methodology is presented to develop hierarchical Petri net models that scale in fidelity. Elementary fragments represent failures and redundancy. Subsystem modules can be substituted for more detailed models. Analysis and simulation assess system reliability and failure response. This supports designing ultra-reliable systems to safely sustain human life in space.

Abstract 196: In vitro modeling of pediatric solid tumor lung metastases

Abstract Metastasis remains the main cause of death in pediatric cancer patients with the lung being one of the most common affected organs. Our inability to cure these patients is largely due to insufficient knowledge about tumor and metastatic niche plasticity, while existing models are not fully effective in mirroring the response seen in clinical setting. Our goal is to overcome these limitations by establishing in vitro lung metastasis models using tumor/lung organoid co-cultures to study lung infiltration of pediatric solid tumors. We successfully established patient-derived lung organoids from pediatric lung tissue and characterized them according to the presence and the localization of the respective lung epithelial cell types. Co-culture conditions of lung organoids with PDX-derived Ewing sarcoma and osteosarcoma cells were optimized and models established, while the establishment of models for other pediatric solid tumor entities is ongoing. We have observed infiltration of the lung organoids by tumor cells, and our preliminary findings suggest distinct patterns of infiltration among different tumor entities. Furthermore, we have performed single-cell RNA sequencing analysis on these co-cultures in comparison to the parental lung organoids and tumor cells, aiming to uncover the specific signaling pathways activated in the lung metastatic niche in response to tumor cell invasion. Additionally, experiments using conditioned medium suggest that the lung organoid secretome is sufficient to induce homing of osteosarcoma and Ewing sarcoma cells to the organoids, with the CXCL12/CXCR4 signaling axis as a prime candidate driver. To ascertain the extent to which our in vitro model recapitulates the in vivo lung metastatic niche, we performed spatial transcriptomics (using VISIUM/10X Genomics) on formalin-fixed paraffin-embedded (FFPE) tissue blocks of paired primary tumors and lung metastasis samples for Ewing sarcoma and osteosarcoma. Comprehensive data analysis is currently ongoing, which will instruct a stepwise incorporation of additional factors into our modular organoid co-culture model, resulting in a better representation of the lung metastatic niche. Further, the analysis of patient-derived material will elucidate the spatial organization of solid tumor lung metastases and contribute to the identification of signaling pathways implicated in lung infiltration. In conclusion, our study not only unravels the complexities of pediatric solid tumor metastasis, but also lays the foundation for exploring the anti-metastatic potential of pathway-specific compounds targeting tumor/lung interactions using the established in vitro lung metastasis models. This study is supported by grant 35353-B of the Austrian Science Fund. Citation Format: Martha Zylka, Christoph Hafemeister, Lukas Watzke, Ulrike Mann, Didier Surdez, E. Alejandro Sweet-Cordero, Bernadette Liegl-Atzwanger, Matthias Dettmer, Matthias Farlik, Florian Halbritter, Martin Metzelder, Heinrich Kovar, Branka Radic-Sarikas. In vitro modeling of pediatric solid tumor lung metastases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 196.

Mapping out focus for circular economy business models (CEBMs) research in construction sector studies – a bibliometric approach

Purpose The circular economy business models (CEBMs) provide ways for firms operating in the construction industry to move from a linear to a circular approach. Thus, this study aims to explore CEBM research within the construction sector to show the focus area of studies, highlighting new areas that require attention. Design/methodology/approach This study adopted a bibliometric approach, using the Scopus database as the data source. The keywords used for paper extraction from the database were “circular economy business” OR “circular business” AND “model” OR “models” AND “construction industry” OR “building industry”. The VOSviewer software was then used to prepare a co-occurrence and co-authorship map based on the bibliographic data gathered. Findings The study’s findings reveal five research clusters in the construction industry. These clusters include circular construction intelligence, modular business modelling, eco-construction, sustainable construction economics and smart energy-efficient buildings. The two most cited scholars had two publications each, while the top journals are the Journal of Cleaner Production and Sustainable Production and Consumption. This study concludes that there is a need for research within the construction sector to focus on CEBMs’ archetypes and frameworks. This will enable a smooth transition from linear to circular business models in the sector. Research limitations/implications The information was gathered from a single database, Scopus; hence, using other databases, including Web of Science, Google Scholar and Dimensions, might produce more articles for examination and, consequently, different findings on the subject under investigation. Practical implications These findings would assist researchers in considering the areas mentioned, which are yet to receive attention, and, by extension, enhance economic development while maintaining environmental sustainability. Originality/value This paper made a significant contribution to the body of knowledge by identifying scholars and platforms that have been instrumental in advancing CEBM research and highlighting new areas that require attention in the construction sector.

Dynamic joint decision of matching parameters and relocation strategies in ride-sourcing systems interacting with traffic congestion

As the ride-sourcing market expands, ride-sourcing fleets have increased urban traffic congestion, and in turn, road congestion is affecting ride-sourcing operations. It is crucial to incorporate this interaction mechanism into the operational decision of ride-sourcing systems. This mechanism can be described in detail by simulation models. Applying simulation-based optimization methods to the real-time operation of ride-sourcing systems is challenging due to the limitations of simulation efficiency. To tackle this issue, this study first proposes a modular simulation model combining time-driven and event-driven mechanisms. The simulation model comprises two layers: the traffic flow module at the bottom, defined by trip-based and multi-region macroscopic fundamental diagrams and cell transmission models, and the ride-sourcing operation module at the top, which considers the interaction between the traffic congestion and ride-sourcing operation and models the random behavior of passengers and drivers. We verify the efficiency and accuracy of the simulation model. The simulation model is utilized as an evaluator of the objective functions and performance measures. Then, we integrate the Bayesian optimization, parallel sampling, and rolling horizon approaches to develop an efficient and effective simulation-based optimization framework for the dynamic joint decision-making of matching radius, matching intervals, and threshold relocation strategies. Six groups of experiments for the traffic scenario in Berlin reveal some interesting findings. (1) The matching rate first increases and then decreases with the matching radius (a concave function), while the closest study does not think so. (2) As the fleet size grows, passenger waiting time reaches its minimum and then rises because of the increased endogenous congestion generated by ride-sourcing fleets. (3) The optimal operation strategy considering endogenous congestion not only leads to an increase in the system revenue and efficiency but also leads to congestion relief, even though the latter was not our initial objective. This benefit is the most pronounced when the fleet size and background traffic are moderate.

Working mechanism evaluations of full-scale joints with bolted-cover plate connection for modular steel buildings

The force-reliability of the modular structural joints is crucial for ensuring the structural integrity of modular steel buildings. However, the welds connecting the beam and column within the module are susceptible to tear during seismic events. This mode of failure greatly undermines the ability of these joints to withstand seismic forces. Four full-scale modular structural joints with bolted-cover plate connection were designed and conducted for seismic performance testing, emphasizing the significance of methods such as reinforcing diagonal braces and strengthening flanges on the protective effect of beam–column welds in the module. The simplified modular structural joint and frame finite element model were proposed based on experimental data, refined finite element modeling, and theoretical analysis. The findings suggest that the seismic behavior of the modular structural joint remains unaffected by variations in axial compression ratio within the designed range of parameters. The beam–column weld of the module in the reinforced joint exhibits almost no weld tearing, and both strengthening methods demonstrate exceptional capacity for energy dissipation. The proposed simplified modeling method facilitates the efficient determination of the modular structural joint bearing capacity and the lateral stiffness of the modular frame. The research findings presented in this paper can serve as a valuable reference point for the engineering design of modular steel structures.

«Hierarchical» and «Modular» Models of Psychopathological Syndromes and Mental Functions

The aim was to compare «hierarchical» and «modular» models of the mental functions and psychopathological syndromes.Material and method: a historical analysis is undertaken in the narrative review the works of thinkers of different times who put forward the concepts of mental deviations from the norm. Discussion and conclusion: hierarchical models go back to the concepts of the ancient Greek philosopher Plato, modular models – to the concepts of the German doctor F. Gall. The most famous hierarchical model of «circles» of positive and negative general psychopathological syndromes in Russian psychiatry by A.V. Snezhnevsky was preceded by the hierarchical model of M.O. Gurevich – M.Ya. Sereisky, in turn, based on the model of «levels» of the psyche of the English neurologist J.H. Jackson and E. Kraepelin’s «organ registers» model. In German psychiatry also K. Jaspers cited the «onion» model in the first edition of General Psychopathology, substantiating the complication of psychopathological symptoms depending on the nosology of mental disorders. Later, the American psycholinguist and philosopher J. Fodor proposed a «modular» model of the psyche, according to which the human psyche consists of relatively independent «modules» («encapsulated») that are specific to a certain area of stimuli, are genetically determined, correlate with certain neural structures and are «computationally autonomous». The concept of modular construction of the psyche was further developed in the works of psychologists and psychiatrists of the «evolutionary» direction (models of «massive modularity», which denied the «encapsulation» of modules according to J. Fodor), based, among other premises, on the modular construction of the brain of many animal species. Diversity turns out to be inherent not only in modular models of the psyche, but also in hierarchical ones, for example, the sequence of general psychopathological positive syndromes in A.V. Snezhnevsky’s model of «circles» differs from the correlation of psychopathological syndromes in the model of «registers» by E. Kraepelin, who at the final stage of his scientific activity postulated the principles of «comparative psychiatry», in many respects similar to the principles of the subsequent direction of «evolutionary» psychiatry.

Revised Magnetospheric Model Reveals Signatures of Field‐Aligned Current Systems at Mercury

AbstractMercury is the smallest and innermost planet of our solar system and has a dipole‐dominated internal magnetic field that is relatively weak, very axisymmetric and significantly offset toward north. Through the interaction with the solar wind, a magnetosphere is created. Compared to the magnetosphere of Earth, Mercury's magnetosphere is smaller and more dynamic. To understand the magnetospheric structures and processes we use in situ MESSENGER data to develop further a semi‐empiric model of the magnetospheric magnetic field, which can explain the observations and help to improve the mission planning for the BepiColombo mission en‐route to Mercury. We present this semi‐empiric KTH22‐model, a modular model to calculate the magnetic field inside the Hermean magnetosphere. Korth et al. (2015, https://doi.org/10.1002/2015JA021022, 2017, https://doi.org/10.1002/2017gl074699) published a model, which is the basis for the KTH22‐model. In this new version, the representation of the neutral sheet current magnetic field is more realistic, because it is now based on observations rather than ad‐hoc assumptions. Furthermore, a new module is added to depict the eastward ring shaped current magnetic field. These enhancements offer the possibility to improve the main field determination. In addition, analyzing the magnetic field residuals allows us to investigate the field‐aligned currents and their possible dependencies on external drivers. We see increasing currents under more disturbed conditions inside the magnetosphere, but no clear dependence on the z‐component of the interplanetary magnetic field nor on the magnetosheath plasma β.

Quantitative assessment of food safety interventions for Campylobacter spp. and Salmonella spp. along the chicken meat supply chain in Burkina Faso and Ethiopia

Rural and small-scale chicken farming is a major source of income in most African countries, and chicken meat is an important source of nutrients. However, chicken meat can be contaminated with Campylobacter spp. and Salmonella spp., pathogens with a high reported burden of foodborne illnesses. Therefore, it is essential to control these pathogens in chicken meat. Quantitative microbial risk assessments (QMRA) can aid the development of effective food safety control measures and are currently lacking in chicken meat supply chains in the African context. In this study, we developed stochastic QMRA models for Salmonella spp. and Campylobacter spp. in the chicken meat supply chain in Burkina Faso and Ethiopia employing the modular process risk model in @Risk software. The study scope covered chicken farming, transport, slaughtering, consumer handling, and consumption. Effectiveness of candidate interventions was assessed against baseline models' outputs, which showed that the mean annual Campylobacter spp. risk estimates were 6482 cases of illness per 100,000 persons and 164 disability adjusted life years (DALYs) per 100,000 persons in Burkina Faso, and 12,145 cases and 272 DALYs per 100,000 persons in Ethiopia. For Salmonella spp., mean annual estimates were 2713 cases and 1212 DALYs per 100,000 persons in Burkina Faso, and 4745 cases and 432 DALYs per 100,000 persons in Ethiopia. Combining interventions (improved hand washing plus designated kitchen utensils plus improved cooking) resulted in 75 % risk reduction in Burkina Faso at restaurants and 93 to 94 % in Ethiopia at homes for both Salmonella spp. and Campylobacter spp. For Burkina Faso, adding good hygienic slaughter practices at the market to these combined interventions led to over 91 % microbial risk reduction. Interventions that involved multiple food safety actions in a particular step of the supply chain or combining different interventions from different steps of the supply chain resulted in more risk reduction than individual action interventions. Overall, this study demonstrates how diverse and scanty food supply chain information can be applied in QMRA to provide estimates that can be used to stimulate risk-based food safety action in African countries.

Quark-lepton mass relations from modular flavor symmetry

The so-called Golden Mass Relation provides a testable correlation between charged-lepton and down-type quark masses, that arises in certain flavor models that do not rely on Grand Unification. Such models typically involve broken family symmetries. In this work, we demonstrate that realistic fermion mass relations can emerge naturally in modular invariant models, without relying on ad hoc flavon alignments. We provide a model-independent derivation of a class of mass relations that are experimentally testable. These relations are determined by both the Clebsch-Gordan coefficients of the specific finite modular group and the expansion coefficients of its modular forms, thus offering potential probes of modular invariant models. As a detailed example, we present a set of viable mass relations based on the Γ4 ≅ S4 symmetry, which have calculable deviations from the usual Golden Mass Relation.

Quality of Life in Rural Areas: A Set of Indicators for Improving Wellbeing

Quality of life can be generally defined as people’s satisfaction with their lives and personal wellbeing. Contemporary literature agrees that dimensions such as health, education, employment, leisure, social relations, security, environment, landscape, and cultural heritage should be considered. Tourism serves as a stimulus for rural development, and assessing residents’ and tourists’ quality of life is relevant for local administrators of a tourist destination. Given the absence of quality-of-life models for individual municipalities, the research questions were aimed at the mapping of quality-of-life frameworks and the construction of a set of quality-of-life indicators for Alagna Valsesia. This research was conducted in 2023. The results of the research showed the possibility of constructing a modular model of indicator sets aimed particularly at decision making by territorial policymakers. The limitations of the research are related to the difficulty of finding different indicators in public platforms and, in the future, we would like to build a synthetic indicator replicable in other Piedmontese and Italian municipalities.

Hemodialysis Wastewater Treatment via Electrocoagulation and Electro-Oxidation: Modular Pilot-Level Modeling and Simulation.

Hemodialysis treatment in specialized clinics within the same hospital significantly impacts environmental water health due to contaminated wastewater. The issues observed included changes in electrical conductivity, the presence of dangerous bacterial loads, toxicity from heavy metals, total cyanide content, and helminth parasite eggs. The level of damage is dependent on the patient's health under treatment. This research will use a modular system that employs electrocoagulation and electro-oxidation processes at the laboratory and pilot levels to treat hemodialysis wastewater using synthetically prepared and real samples extracted from local clinics. The results showed that these hybrid systems improved various physicochemical parameters. Specifically, decreases in electrical conductivity of 49 %, total suspended solids of 27-100 %, chemical oxygen demand of 49 %, biochemical oxygen demand of 49 %, and cation and anion loading were observed at 96-100 % and pH 8.13 UpH in accordance with the established standards. With these results and the experimental conditions used, the proposed treatment system was modeled using the GPS-X program, and it was concluded that the modular system used and the electrocoagulation/electro-oxidation/activated carbon configuration is suitable for treating wastewater from hemodialysis and that scaling up this process to facilities that have dialysate machines more advanced than those considered in this work is possible.

Surgical Medical Education via 3D Bioprinting: Modular System for Endovascular Training.

There is currently a shift in surgical training from traditional methods to simulation-based approaches, recognizing the necessity of more effective and controlled learning environments. This study introduces a completely new 3D-printed modular system for endovascular surgery training (M-SET), developed to allow various difficulty levels. Its design was based on computed tomography angiographies from real patient data with femoro-popliteal lesions. The study aimed to explore the integration of simulation training via a 3D model into the surgical training curriculum and its effect on their performance. Our preliminary study included 12 volunteer trainees randomized 1:1 into the standard simulation (SS) group (3 stepwise difficulty training sessions) and the random simulation (RS) group (random difficulty of the M-SET). A senior surgeon evaluated and timed the final training session. Feedback reports were assessed through the Student Satisfaction and Self-Confidence in Learning Scale. The SS group completed the training sessions in about half time (23.13 ± 9.2 min vs. 44.6 ± 12.8 min). Trainees expressed high satisfaction with the training program supported by the M-SET. Our 3D-printed modular training model meets the current need for new endovascular training approaches, offering a customizable, accessible, and effective simulation-based educational program with the aim of reducing the time required to reach a high level of practical skills.

Immediate Processing of Sentences in Language Communication

Sentence processing is a fundamental and critical area of inquiry within the field of language processing, as it plays an essential role in facilitating effective communication. The present study focuses on the immediate processing of sentences in English language communication. The article begins by providing an overview of the basic principles underlying sentence processing. It then delves into the various parsing strategies, including the late closure strategy and the minimal attachment strategy. The modular and interactive models of sentence processing are also presented and discussed. Additionally, the relationship between sentence processing and meaning is explored, with an examination of the role of factors such as presupposition and plausibility in language communication process. Finally, the role of prosody in language processing is expounded upon. The paper draws several conclusions regarding the nature of immediate sentence processing in language communication.

Modelling and fault analysis of APROS-based moisture separation reheater

A modular modelling approach was adopted to build a dynamic simulation model of the moisture separation reheater on a high-precision APROS real-time platform to investigate the dynamic operating characteristics of the moisture separation reheater. The model was subjected to steady-state and step dynamic tests at different loads. The results show that the established model can correctly reflect the steam flow and heat transfer properties and can meet the requirements of the simulation. Using the one-dimensional distribution of the model, the effect of a small breakage failure in the heat exchanger bundle was further investigated. The results showed that the heat transfer tube bundle had leaks, reducing the heat transfer capacity and affecting the quality of the steam used to work in the low-pressure turbine. Simultaneously, the effect on steam outlet parameters increased with the degree of leakage in the heat exchanger.

A Predictive Model of Vaccine Reactogenicity Using Data from an InVitro Human Innate Immunity Assay System.

A primary concern in vaccine development is safety, particularly avoiding an excessive immune reaction in an otherwise healthy individual. An accurate prediction of vaccine reactogenicity using invitro assays and computational models would facilitate screening and prioritization of novel candidates early in the vaccine development process. Using the modular invitro immune construct model of human innate immunity, PBMCs from 40 healthy donors were treated with 10 different vaccines of varying reactogenicity profiles and then cell culture supernatants were analyzed via flow cytometry and a multichemokine/cytokine assay. Differential response profiles of innate activity and cell viability were observed in the system. In parallel, an extensive adverse event (AE) dataset for the vaccines was assembled from clinical trial data. A novel reactogenicity scoring framework accounting for the frequency and severity of local and systemic AEs was applied to the clinical data, and a machine learning approach was employed to predict the incidence of clinical AEs from the invitro assay data. Biomarker analysis suggested that the relative levels of IL-1B, IL-6, IL-10, and CCL4 have higher predictive importance for AE risk. Predictive models were developed for local reactogenicity, systemic reactogenicity, and specific individual AEs. A forward-validation study was performed with a vaccine not used in model development, Trumenba (meningococcal group B vaccine). The clinically observed Trumenba local and systemic reactogenicity fell on the 26th and 93rd percentiles of the ranges predicted by the respective models. Models predicting specific AEs were less accurate. Our study presents a useful framework for the further development of vaccine reactogenicity predictive models.

Modular flavor models with positive modular weights: a new lepton model building

We propose an interesting assignment of positive modular weights for fields in a modular non-Abelian discrete flavor symmetry. By this assignment, we can construct inverse seesaw and linear seesaw models without any additional symmetries which possess good testability in current experiments. At first, we discuss possibilities for positive modular weights from a theoretical point of view. Then we show concrete examples of inverse seesaw and linear seesaw scenarios applying modular A4 symmetry as examples and demonstrate some predictions as well as consistency with experimental results such as neutrino masses and mixings.

Application of (bio) chemical engineering concepts and tools to model genetic regulatory circuits, and some essential central carbon metabolism pathways in living cells. Part 4. Applications in the design of some Genetically Modified Micro-Organisms (GMOs)

In the first part of this work, the general Chemical and Biochemical Engineering (CBE) concepts and rules are briefly reviewed, together with the rules of the control theory of Nonlinear Systems (NSCT), all in the context of (i) deriving deterministic Modular Structured Kinetic Models (MSDKM) to describe the dynamics of metabolic processes in living cells, and (ii) of Hybrid Structured Modular Dynamic Models (HSMDM) (with continuous variables, linking the cell-nano-scale MSDKM state variables to the macro-scale state variables of the bioreactor dynamic model). Thus, in the HSMDM model, both prediction quality and its validity range are improved. By contrast, the current (classical/default) approach in bioengineering practice for solving design, optimization, and control problems based on the math models of industrial biological reactors is to use unstructured Monod (for cell culture reactor) or simple Michaelis-Menten (if only enzymatic reactions are retained) global kinetic models by ignoring detailed representations of metabolic cellular processes. By contrast, as reviewed, and exemplified in the second part of this work, an accurate and realistic math modelling of the dynamic individual GERMs (gene expression regulatory module), or genetic regulatory circuits (GRC), and cell-scale CCM (central carbon metabolism) key-modules can be done by only using the novel holistic ’Whole-Cell Of Variable-Volume’ (WCVV) modelling framework, under isotonic/homeostatic conditions/constraints introduced and promoted by the author. An example was given in the same Part 2 for the case study of a dynamic model for the oscillating glycolysis coupled with the Tryptophan (TRP) oscillating synthesis in the E. coli cells.

Research on fuel injection characteristics of common rail system based on high pressure pipeline integration and matching

AbstractThe modular prediction model of high pressure common rail system was established to study the influence of high‐pressure pipeline integration matching on the fuel injection characteristics of common rail system. The influence of common rail volume on pressure building and pressure fluctuation in common rail tubes was analyzed. The influence of common rail volume on the matching of fuel injection frequency (number of fuel injectors) and fuel supply frequency (number of plunger pumps) was studied by using the control variable method, and the basic optimal solution of the system was obtained. The influence of the common rail structure on the fuel flow characteristics of the system was also studied. The matching relationship between high pressure tubing and common rail system is studied by introducing dimensionless numbers such as length‐diameter ratio of pipeline. The results demonstrate that the increase of the storage space of the accumulator can effectively reduce the fluctuation in the system, so that the injection volume increases slowly and then decreases rapidly, with a slope of −5.70 × 10−3 mm3. The increase of the diameter of the common rail makes the fuel flow characteristics become good first and then bad, and the increase of the length of the common rail can soothe the pressure fluctuations. The increase of the diameter of the link tube (LT) makes the fuel injection volume of the injector increase first and then decrease. The optimal VR solution for the LT is 0.0249 and the optimal ratio of the length to diameter of a pipeline solution is 55.10. The structure of the distribution tube and its matching to the common rail have little effect on the fuel flow characteristics. When the diameter and length of the injection tube are too large, the influence on the injection pressure of the injector is negatively correlated.