Mathematical Model Research Articles

Hygrothermal buckling analysis of thin rectangular FGM plate with variable thickness

PurposeThis paper aims to contribute novel insights into the analysis of thin functionally graded material (FGM) plates with variable thickness, considering both temperature-dependent and independent material properties, focusing on critical linear buckling temperature rise and the effect of critical linear moisture for various moisture concentrations.Design/methodology/approachThe study derives stability and equilibrium equations for thin rectangular FGM plates under hygrothermal loading, employing classical plate theory (CPT). Buckling behavior is examined using Galerkin’s method to obtain pre-buckling force resultants.FindingsThe findings highlight significant increases in critical buckling temperature with aspect ratio, distinct temperature sensitivity between materials and increasing moisture susceptibility with larger aspect ratios. These insights inform material selection and design optimization for FGM plates under hygrothermal loading, enhancing engineering applications.Research limitations/implicationsThis research primarily focuses on hypothetical scenarios and mathematical model development and analysis.Originality/valueThis paper presents original contributions in the field by addressing the hygrothermal buckling analysis of thin FGM rectangular plates with variable thickness, utilizing CPT, thereby enriching the understanding of structural behavior in varying environmental conditions.

Non-linear modeling and parameter identification of a bolted joint using substructure synthesis theory

Abstract Engineering applications require accurate modeling and parameter identification to anticipate bolted joint behavior under different loading circumstances. Bolted joints are extensively used in civil and mechanical structures. In this research study, cubic stiffness non-linearity is examined and a comprehensive model, which can exhibit the non-linearity of joint behavior, is developed. This is achieved by modeling the bolted joint which is connected at one end of a cantilever beam. Mathematical model is established using concept of sub structure synthesis theory by considering non-linear translational stiffness and non-linear rotational stiffness as a boundary condition. Non-dimensional natural frequencies are estimated by assuming stiffness parameters and joint parameter estimation for translational spring having nonlinear stiffness is calculated using second order curve fitting technique. Furthermore, estimated and exact value of cubic stiffness coefficient are compared. The experimental results shows that the percentage error of estimation for all the modes are less than 8%. The experimentally determined natural frequencies are further contrasted with an analytical results to validate a precision of generated model. Present work contributes in improving the bolted joint analysis by providing a solid non-linear modeling and parameter identification methodology. This methodology enhances design practices and ensures the durability of engineering structures and mechanical systems by improving bolted joint comprehension.

Advanced mathematical modeling of hepatitis B transmission dynamics with and without diffusion effect using real data from Thailand

Advanced mathematical modeling of hepatitis B transmission dynamics with and without diffusion effect using real data from Thailand

The effect of temperature on the boundary conditions of West Nile virus circulation in Europe.

West Nile virus (WNV) is a vector-borne flavivirus that causes an increasing number of human and equine West Nile fever cases in Europe. While the virus has been present in the Mediterranean basin and the Balkans since the 1960s, recent years have witnessed its northward expansion, with the first human cases reported in Germany in 2018 and the Netherlands in 2020. WNV transmission and amplification within mosquitoes are temperature-dependent. This study applies a mathematical modelling approach to assess the conditions under which WNV circulation occurs based on the proportion of mosquito bites on WNV-competent birds (dilution), vector-host ratios, mosquito season length and the observed daily temperature data. We modelled five distinct European regions where previous WNV circulation has been observed within the Netherlands, Germany, Spain, Italy, and Greece. We observed that the number of days in which the basic reproduction number (R0) is above one, increased over the last 40 years in all five regions. In the Netherlands, the number of days in which the R0 is above one, is 70% lower than in Spain. The temperature in Greece, Spain and Italy allowed for circulation under low vector-host ratios, and at a high dilution. On the other hand in the Netherlands and Germany, given the observed daily temperature, the thresholds for circulation requires a lower dilution and higher vector-host ratios. For the Netherlands, a short window of introductions between late May and mid-June would result in detectable outbreaks. Our findings revealed that the temperate maritime climate of the Netherlands allows WNV circulation primarily during warmer summers, and only under high vector-host ratios. This research contributes valuable insights into the dynamic relationship between temperature, vector properties, and WNV transmission, offering guidance for proactive strategies in addressing this emerging health threat in Europe.

Decoding immune kinetics: unveiling secrets using custom-built mathematical models.

Decoding immune kinetics: unveiling secrets using custom-built mathematical models.

Rice husk reuse as a sustainable energy alternative in Tolima, Colombia

Colombia has great potential to produce clean energy through the use of residual biomass from the agricultural sector, such as residues obtained from the life cycle of rice production. This document presents a mixed approach methodology study to examine the combustion of rice husks as a possible energy alternative in the Tolima department of Colombia. First, the physicochemical characteristics of the rice husk were analyzed to characterize the raw material. Next, System Advisor Model (SAM) software was used to model a bioenergy plant to obtain biochar, bio-oil, and biogas from the combustion of rice husks and generate performance matrices, such as thermal efficiency, heat rate, and capacity factor. Then, the project was evaluated for financial feasibility using a mathematical model of net present value (NPV) with a planning horizon of 5 years. Finally, a subset of the local population was surveyed to assess perspectives on the project in the region. The results of the rice husk physicochemical analysis were the following: nitrogen content (0.74%), organic carbon (38.04%), silica (18.39%), humidity determination (7.68%), ash (19.4%), presence of carbonates (< 0.01%), and pH (6.41). These properties are adequate for the combustion process. The SAM simulation showed that the heat transferred in the boiler was 3180 kW, maintaining an efficiency between 50 and 52% throughout the 12 months of the year, meaning that the rice husk can generate electricity and thermal energy. The financial analysis showed that the internal rate of return (IRR) was 6% higher than the opportunity interest rate (OIR), demonstrating economic feasibility of the project. The design and creation of a rice husk processing plant is socially and environmentally viable and has the potential to contribute to the economic development of the Tolima community and reduce greenhouse gases. Likewise, this activity has the potential to promote energy security for consumers and environmental sustainability while at the same time being economically competitive.

Mathematical modeling and control of Covid‐19

In this paper, the author proposes and studies a mathematical model for the spread of coronavirus 2019. The effect of preventive programs on the control of disease is also considered. The basic reproduction number was computed and the results showed that forward bifurcation occured. Local and global stability of the equilibrium points of the model was studied by geometric stability method and Lyapunov function. Finally, the particular data of China which was reported for Covid‐19 were used for numerical simulation.

Vacuum microwave drying of PEF-pretreated Chilean abalone (Concholepas Concholepas) slices: drying features, sustainability parameters, and protein quality properties

A pulsed electric field (PEF: 2.0 kV/cm) was applied before vacuum microwave drying (VMD: 120 W, 120/260 W, and 260 W at 40 kPa) on Chilean abalone mollusks. PEF and VMD effects on process features (drying kinetics, modeling, and sustainability) and product quality (texture, structure, and digestibility) were measured. The PEF application increased moisture diffusivity by up to 27% in the combined PEF+VMD process. According to the statistical analysis applied to all mathematical models, the Logarithmic model was best fitted to VMD experimental values. In terms of energy consumption, applying PEF+VMD reduced energy consumption by up to 33% of the 120W and 120/260W non-PEF samples. The best values for the rehydration index were obtained with the 120/260W (45%) and PEF+120/260W (61%) treatments. In addition, these samples had the best texture parameters. The PEF+120/260W treatment showed the highest degree of hydrolysis (11%) for the calculated protein efficiency. Finally, using PEF as a pretreatment in a VMD process can be cost-effective for scale replication due to its time efficiency and product quality to Chilean abalone samples.Graphical

Analysis of the influence of the metal wheel radial stiffness on traction characteristics

BACKGROUND: The traction characteristic of a wheel mover depends both on its type and rigidity properties, and on the physico-mechanical soil properties. The combined use of the discrete element method to describe the soil and the finite element method to model the wheel makes it possible to specify and expand the existing empirical models of the interaction of the mover with the ground. The application of this method will reduce the amount of full-scale testing required to verify the interaction model. AIMS: Development the traction characteristic of a metal wheel by varying its design parameters. METHODS: To develop a mathematical model of a metal wheel and determine traction characteristics, numerical methods of discrete and finite elements are used. RESULTS: In this paper, a metal wheel mathematical model with ability to vary the thickness of the elastic sidewall was developed. Radial stiffness characteristics were obtained for three wheel samples. The developed mathematical model of the interaction of a wheel mover with a ground is based on the application of discrete and finite element methods. In this paper, a proportional controller was used to application of forces to the wheel mover. The dependences of the longitudinal reaction coefficient on the slip coefficient were obtained and a comparative analysis of the radial stiffness influence on traction characteristics was carried out. CONCLUSIONS: The combined application of the discrete and finite element methods will make it possible to determine the traction characteristics of the movers of various designs when interacting with a deformable soil and to evaluate the influence of its design parameters on it.

PSV-16 Effect of precision feeding and functional amino acids on immune response and protein metabolism of growing pigs raised in poor sanitary conditions

Abstract The activation of the immune system reduces the nutrient availability for growth and increases the variability among pigs. Functional amino acids (AA) supplementation can reduce the negative effects of immune activation. Additionally, providing daily tailored diets using individual precision feeding (IPF) was shown to account for individual variability. Therefore, we hypothesized that the association of IPF and functional AA supplementation could reduce the negative effect of immune-challenged pigs fed with daily tailored diets. The aim of this study was to assess performance and blood parameters variation of growing pigs under poor sanitary conditions while being fed functional AA 120% above the estimated INRA AA ratios within IPF, compared with a conventional group-phase (GP) feeding system. The sanitary condition was characterized by oral inoculation of 2 × 109 cfu of Salmonella typhimurium and manure spreading on the pen floor on d 0. Sixty gilts (23 ± 2.8 kg body weight; BW) were distributed in a complete randomized block design in a 2 x 2 factorial arrangement composed of 2 diets: CN with 100% INRA AA ratio or AA+ with 120% of the ratio for Met, Thr and Trp; and 2 feeding systems: GP or IPF. GP pigs received a single diet matching the SID Lys requirement of the 80th-percentile pig at the beginning of the trial whereas IPF pigs received a diet tailored daily to each pig requirement. All pigs were group-housed and fed ad libitum for 28 d by automatic feeders. Body weight was measured at d 0 and 28 and feed intake was recorded daily. Blood samples were collected at d 0, 7 and 28. Data were analyzed with diet and feeding systems and their interactions as fixed effects and BW blocks as random effect. Blood parameters were analyzed as repeated measurements over time. The pig was considered the experimental unit. No diet effect or interactions were observed for any variable (P &amp;gt; 0.05), suggesting that only supplementing Met, Trp, and Thr is not enough to support growth during a sanitary challenge (Table 1). Haptoglobin and IgG increased linearly whereas IgA, urea, and creatinine had a quadratic increase over time (P &amp;lt; 0.05; Table 2). The IPF decreased growth performance and increased serum IgA and creatinine (P &amp;lt; 0.05), mostly due to the fact that IPF reduces AA provision compared with GP system. The IPF model, as most mathematical models, does not account for the AA and energy costs related to the immune challenge. Therefore, IPF might have underestimated the requirements of the pigs, and limited the amount of nutrients provided. In conclusion, the combined effect of IPF and functional AA supplementation was not able to reduce the negative effect of the sanitary challenge.

Hybrid modeling of an ultracentrifugation process for separation of full and empty adeno-associated virus particles.

Ultracentrifugation is an attractive method for separating full and empty capsids, exploiting their density difference. Changes of the serotype/capsid, density of loading material, or the genetic information contained in the adeno-associated viruses (AAVs) require the adaptation of the harvesting parameters and the density gradient loaded onto the centrifuge. To streamline these adaptations, a mathematical model could support the design and testing of operating conditions.Here, hybrid models, which combine empirical functions with artificial neural networks, are proposed to describe the separation of full and empty capsids as a function of material and operational parameters, i.e., the harvest model. In addition, critical quality attributes are estimated by a quality model which is operating on top of the harvest model. The performance of these models was evaluated using test data and two additional blind runs. Also, a "what-if" analysis was conducted to investigate whether the models' predictions align with expectations.It is concluded that the models are sufficiently accurate to support the design of operating conditions, though the accuracy and applicability of the models can further be increased by training them on more specific data with higher variability.

Development of Chlorhexidine-Loaded Lipid Nanoparticles Incorporated in a Bioceramic Endodontic Sealer.

This study aimed to assess BioRoot RCS (BR) incorporating liposomal chlorhexidine digluconate (CHX) for its antibacterial activity, drug release capacity, and physicochemical properties. Drug release of CHX liposomal formulations in combination with BR was evaluated spectrophotometrically and through mathematical release models for 30 days. A selected combination was evaluated for antimicrobial properties against Enterococcus. faecalis (E. faecalis) biofilm growth on human dentin. Cytotoxicity was assessed following the ISO 10993-5:2019 standard on days 1, 3, and 7. Physicochemical properties were evaluated through setting time, Fourier transform infrared spectroscopy (FTIR), solubility, contact angle, and film thickness. From BR, liposomal CHX released up to 7-fold higher CHX than CHX solution (p<0.05), following a triphasic drug release pattern compared to the CHX solution, which followed a quasi-Fickian diffusion. BR combined with a selected liposomal CHX completely inhibited E. faecalis biofilm growth compared to the combination of BR with CHX solution and the control group (p<0.05). Liposomal CHX decreased the contact angle (p<0.05) and solubility but increased cytotoxicity (p<0.05) of BR, staying above the ISO threshold. None of the other physicochemical characteristics tested differed from BR (p>0.05). This liposomal formulation improved CHX release from BR, enhancing the antibacterial effectiveness. It presents a promising approach for local anti-biofilm therapy in endodontics without substantially altering the physicochemical characteristics of BR.

A quaternion-based mathematical model for geometrically exact dynamic analysis of cantilevered pipe conveying fluid

A quaternion-based mathematical model for geometrically exact dynamic analysis of cantilevered pipe conveying fluid

Modeling and predicting individual variation in COVID-19 vaccine-elicited antibody response in the general population.

As we learned during the COVID-19 pandemic, vaccines are one of the most important tools in infectious disease control. To date, an unprecedentedly large volume of high-quality data on COVID-19 vaccinations have been accumulated. For preparedness in future pandemics beyond COVID-19, these valuable datasets should be analyzed to best shape an effective vaccination strategy. We are collecting longitudinal data from a community-based cohort in Fukushima, Japan, that consists of 2,407 individuals who underwent serum sampling two or three times after a two-dose vaccination with either BNT162b2 or mRNA-1273. Using the individually reconstructed time courses of the vaccine-elicited antibody response based on mathematical modeling, we first identified basic demographic and health information that contributed to the main features of the antibody dynamics, i.e., the peak, the duration, and the area under the curve. We showed that these three features of antibody dynamics were partially explained by underlying medical conditions, adverse reactions to vaccinations, and medications, consistent with the findings of previous studies. We then applied to these factors a recently proposed computational method to optimally fit an "antibody score", which resulted in an integer-based score that can be used as a basis for identifying individuals with higher or lower antibody titers from basic demographic and health information. The score can be easily calculated by individuals themselves or by medical practitioners. Although the sensitivity of this score is currently not very high, in the future, as more data become available, it has the potential to identify vulnerable populations and encourage them to get booster vaccinations. Our mathematical model can be extended to any kind of vaccination and therefore can form a basis for policy decisions regarding the distribution of booster vaccines to strengthen immunity in future pandemics.

Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors before surgery while simultaneously allowing for controlled evaluation of biomarkers, toxicity, and suppression of distant (occult) metastatic disease. Yet neoadjuvant clinical trials are rarely preceded by preclinical testing involving neoadjuvant treatment, surgery, and post-surgery monitoring of the disease. Here we used a mouse model of spontaneous metastasis occurring after surgical removal of orthotopically implanted primary tumors to develop a predictive mathematical model of neoadjuvant treatment response to sunitinib, a receptor tyrosine kinase inhibitor (RTKI). Treatment outcomes were used to validate a novel mathematical kinetics-pharmacodynamics model predictive of perioperative disease progression. Longitudinal measurements of presurgical primary tumor size and postsurgical metastatic burden were compiled using 128 mice receiving variable neoadjuvant treatment doses and schedules (released publicly at https://zenodo.org/records/10607753). A non-linear mixed-effects modeling approach quantified inter-animal variabilities in metastatic dynamics and survival, and machine-learning algorithms were applied to investigate the significance of several biomarkers at resection as predictors of individual kinetics. Biomarkers included circulating tumor- and immune-based cells (i.e., circulating tumor cells and myeloid-derived suppressor cells) as well as immunohistochemical tumor proteins (i.e., CD31 and Ki67). Our computational simulations show that neoadjuvant RTKI treatment inhibits primary tumor growth but has little efficacy in preventing (micro)-metastatic disease progression after surgery and treatment cessation. Machine learning algorithms that included support vector machines, random forests, and artificial neural networks, confirmed a lack of definitive biomarkers, which shows the value of preclinical modeling studies to identify potential failures that should be avoided clinically.

APPLICATION OF HYDROGELS FOR WATER SHUTOFF TREATMENTS. Message No. 2

The article analyzes the use of hydrogels with nanoparticle additives for well water shutoff, as well as the development of a mathematical apparatus for hydrodynamic modeling of water shutoff operations. One of the most significant trends in the development of gel forming compounds for well water shutoff in the last 10 years has been the use of nanocomposites. The base polymers for nanocomposites used for water shutoff operations are either synthetic or biopolymer origin. The article highlights the novelty and prospects of using nanoparticles in sealing compositions. Various nanocomponent additives are used to increase the success of the use of hydrogel polymer systems in order to limit water inflow and expand the scope of their application in complicated reservoir conditions. These include carbon and mineral nanoparticles, which increase the stability and strength of crosslinked gels in formation conditions.In this paper, we consider the optimization of the repair and insulation operations design using gels for well water shutoff using mathematical modeling, which helps to justify the volume of hydrogel injection and calculate the necessary pressure gradients at which the sealing screen remains stable. The paramount importance of determining the source of well flooding is emphasized, depending on which the processing design is already being built, and appropriate materials are selected; trends in the development of repair and insulation operations at the present stage are traced. Based on the results of the implementation of the proposed model by numerical methods, the authors constructed diagrams of the stability of the waterproofing screen depending on the fracture width, screen size, gel injection rate and reservoir permeability. The technique proposed in the work allows to correctly select and optimize the technological parameters of the operation to maintain the stability of the screen in specific geological conditions.Mathematical modeling allows us to strictly justify the volume of injection of the gel screen, increase the technological and economic efficiency of the process, and in large fields — to rank wells according to the priority of processing. Oilfield practice in various regions of the country fully confirms the main conclusions made in this review article. Preliminary mathematical modeling and the introduction of microdispersions into gel formulations can significantly increase the efficiency of water shutoff operations. The next step in the development of water insulation technologies is the use of nanodispersions, which look very promising in laboratory modeling and are no longer exotic materials with unrealistic cost.

Epidemiological and health economic implications of symptom propagation in respiratory pathogens: A mathematical modelling investigation.

Respiratory pathogens inflict a substantial burden on public health and the economy. Although the severity of symptoms caused by these pathogens can vary from asymptomatic to fatal, the factors that determine symptom severity are not fully understood. Correlations in symptoms between infector-infectee pairs, for which evidence is accumulating, can generate large-scale clusters of severe infections that could be devastating to those most at risk, whilst also conceivably leading to chains of mild or asymptomatic infections that generate widespread immunity with minimal cost to public health. Although this effect could be harnessed to amplify the impact of interventions that reduce symptom severity, the mechanistic representation of symptom propagation within mathematical and health economic modelling of respiratory diseases is understudied. We propose a novel framework for incorporating different levels of symptom propagation into models of infectious disease transmission via a single parameter, α. Varying α tunes the model from having no symptom propagation (α = 0, as typically assumed) to one where symptoms always propagate (α = 1). For parameters corresponding to three respiratory pathogens-seasonal influenza, pandemic influenza and SARS-CoV-2-we explored how symptom propagation impacted the relative epidemiological and health-economic performance of three interventions, conceptualised as vaccines with different actions: symptom-attenuating (labelled SA), infection-blocking (IB) and infection-blocking admitting only mild breakthrough infections (IB_MB). In the absence of interventions, with fixed underlying epidemiological parameters, stronger symptom propagation increased the proportion of cases that were severe. For SA and IB_MB, interventions were more effective at reducing prevalence (all infections and severe cases) for higher strengths of symptom propagation. For IB, symptom propagation had no impact on effectiveness, and for seasonal influenza this intervention type was more effective than SA at reducing severe infections for all strengths of symptom propagation. For pandemic influenza and SARS-CoV-2, at low intervention uptake, SA was more effective than IB for all levels of symptom propagation; for high uptake, SA only became more effective under strong symptom propagation. Health economic assessments found that, for SA-type interventions, the amount one could spend on control whilst maintaining a cost-effective intervention (termed threshold unit intervention cost) was very sensitive to the strength of symptom propagation. Overall, the preferred intervention type depended on the combination of the strength of symptom propagation and uptake. Given the importance of determining robust public health responses, we highlight the need to gather further data on symptom propagation, with our modelling framework acting as a template for future analysis.

Bending of Lloyd’s mirror to eliminate the period chirp in the fabrication of diffraction gratings

We present a new technique to prevent the detrimental period chirp that appears in optical gratings fabricated by laser interference lithography (LIL). The idea is to bend the Lloyd’s mirror in the lithographic setup to eliminate the period chirp already at the step of the grating’s exposure. A new mathematical model was developed to describe the required bending geometry of the mirror. It is shown that this geometry can be described by multiple cross-sections of the mirror, each obtained by the solution of an implicit first-order differential equation. The proposed approach is illustrated on the basis of a concrete example. By slightly bending the Lloyd’s mirror (by ≈ 3.5 mm of maximum deflection over an area of 142 mm × 215 mm) the period chirp of the exposed grating can be eliminated completely.

Impact and cost-effectiveness of the 6-month BPaLM regimen for rifampicin-resistant tuberculosis in Moldova: A mathematical modeling analysis.

Emerging evidence suggests that shortened, simplified treatment regimens for rifampicin-resistant tuberculosis (RR-TB) can achieve comparable end-of-treatment (EOT) outcomes to longer regimens. We compared a 6-month regimen containing bedaquiline, pretomanid, linezolid, and moxifloxacin (BPaLM) to a standard of care strategy using a 9- or 18-month regimen depending on whether fluoroquinolone resistance (FQ-R) was detected on drug susceptibility testing (DST). The primary objective was to determine whether 6 months of BPaLM is a cost-effective treatment strategy for RR-TB. We used genomic and demographic data to parameterize a mathematical model estimating long-term health outcomes measured in quality-adjusted life years (QALYs) and lifetime costs in 2022 USD ($) for each treatment strategy for patients 15 years and older diagnosed with pulmonary RR-TB in Moldova, a country with a high burden of TB drug resistance. For each individual, we simulated the natural history of TB and associated treatment outcomes, as well as the process of acquiring resistance to each of 12 anti-TB drugs. Compared to the standard of care, 6 months of BPaLM was cost-effective. This strategy was estimated to reduce lifetime costs by $3,366 (95% UI: [1,465, 5,742] p < 0.001) per individual, with a nonsignificant change in QALYs (-0.06; 95% UI: [-0.49, 0.032] p = 0.790). For those stopping moxifloxacin under the BPaLM regimen, continuing with BPaL plus clofazimine (BPaLC) provided more QALYs at lower cost than continuing with BPaL alone. Strategies based on 6 months of BPaLM had at least a 93% chance of being cost-effective, so long as BPaLC was continued in the event of stopping moxifloxacin. BPaLM for 6 months also reduced the average time spent with TB resistant to amikacin, bedaquiline, clofazimine, cycloserine, moxifloxacin, and pyrazinamide, while it increased the average time spent with TB resistant to delamanid and pretomanid. Sensitivity analyses showed 6 months of BPaLM to be cost-effective across a broad range of values for the relative effectiveness of BPaLM, and the proportion of the cohort with FQ-R. Compared to the standard of care, 6 months of BPaLM would be expected to save Moldova's national TB program budget $7.1 million (95% UI: [1.3 million, 15.4 million] p = 0.002) over the 5-year period from implementation. Our analysis did not account for all possible interactions between specific drugs with regard to treatment outcomes, resistance acquisition, or the consequences of specific types of severe adverse events, nor did we model how the intervention may affect TB transmission dynamics. Compared to standard of care, longer regimens, the implementation of the 6-month BPaLM regimen could improve the cost-effectiveness of care for individuals diagnosed with RR-TB, particularly in settings with a high burden of drug-resistant TB. Further research may be warranted to explore the impact and cost-effectiveness of shorter RR-TB regimens across settings with varied drug-resistant TB burdens and national income levels.

Sequential Transportation of Different Oil Batches through the Industrial Pipeline

In sequential pumping, several liquids with different physical and chemical properties are pumped through one pipeline. The advantages of this method include: using one pipeline to transport different liquids; more complete pipeline loading; and reduced cost of pumping. The paper considers the sequential pumping of two batches of oil blends with different physicochemical properties through an industrial oil pipeline. This is because a batch of high-paraffin oil blend is simultaneously pumped to an oil refinery, and a batch of high-viscosity oil blend is transported further along a pipeline. The difference between the thermal-physical and rheological properties of oil batches imposes a condition on the thermal mode of operation of an industrial pipeline. A mathematical model and algorithm have been created for calculating the sequential transportation of high-paraffin and high-viscosity oil blends. Thermohydraulic calculations of the model show the distribution of hydraulic head, pressure, and temperature of the batches under the operating conditions of pumping units and heating furnaces. The verification and validation of the theoretical analysis was carried out with experimental data measured by the SCADA along the industrial pipeline length. By the thermal mode of sequential pumping, optimal heating temperatures of oil blends were found at the industrial pipeline stations.