Multi-zone Model Research Articles

Kinetic modeling of ion formation during diesel combustion with different fuel injection timing

Ions are formed during the combustion process in internal combustion engines. The measurement of ions inside the combustion chamber produces reliable information about the combustion process. The present study focuses on the formation of ions inside the combustion chamber of diesel engines with different injection timing. For this purpose, a multi-zone thermodynamic model is utilized to simulate the closed cycle of the engine. To understand the kinetic behavior of the ions, the model is connected to an ionic chemical kinetics mechanism with 336 reactions and 81 species. Six important ionic reactions comprising 5 ions are used in the ionic mechanism. Dvode differential equation solver is also employed to calculate the energy and kinetics equations. The developed model has an acceptable accuracy in predicting the performance and pollutants of diesel engines. Based on the results, the ion formation is delayed by delaying the fuel injection timing. The maximum amount of in-cylinder ions depends on injection timing. In-cylinder ion current can predict the start of combustion accurately.

Assessing the effects of transient weather conditions on airborne transmission risk in naturally ventilated hospitals

Many UK hospitals rely heavily on natural ventilation as their main source of airflow in patient wards. This method of ventilation can have cost and energy benefits, but it may lead to unpredictable flow patterns between indoor spaces, potentially leading to the unexpected transport of infectious material to other connecting zones. However, the effects of weather conditions on airborne transmission are often overlooked. A multi-zone CONTAM model of a naturally ventilated hospital respiratory ward, incorporating time-varying weather, was proposed. Coupling this with an airborne infection model, this study assessed the variable risk in interconnected spaces, focusing particularly on occupancy, disease and ventilation scenarios based on a UK respiratory ward. The results suggest that natural ventilation with varying weather conditions can cause irregularities in the ventilation rates and interzonal flow rates of connected zones, leading to infrequent but high peaks in the concentration of airborne pathogens in particular rooms. This transient behaviour increases the risk of airborne infection, particularly through movement of pathogens between rooms, and highlights that large outbreaks may be more likely under certain conditions. This study demonstrated how ventilation rates achieved by natural ventilation are likely to fall below the recommended guidance, and that the implementation of supplemental mechanical ventilation can increase ventilation rates and reduce the variability in infection risks. This model emphasises the need for consideration of transient external conditions when assessing the risk of transmission of airborne infection in indoor environments.

Low Temperature Combustion Modeling and Predictive Control of Marine Engines

The increase of popularity of reactivity-controlled compression ignition (RCCI) is attributed to its capability of achieving ultra-low nitrogen oxides (NOx) and soot emissions with high brake thermal efficiency (BTE). The complex and nonlinear nature of the RCCI combustion makes it challenging for model-based control design. In this work, a model-based control system is developed to control the combustion phasing and the indicated mean effective pressure (IMEP) of RCCI combustion through the adjustments of total fuel energy and blend ratio (BR) in fuel injection. A physics-based nonlinear control-oriented model (COM) is developed to predict the main combustion performance indicators of an RCCI marine engine. The model is validated against a detailed thermo-kinetic multizone model. A novel linear parameter-varying (LPV) model coupled with a model predictive controller (MPC) is utilized to control the aforementioned parameters of the developed COM. The developed system is able to control combustion phasing and IMEP with a tracking error that is within a 5% error margin for nominal and transient engine operating conditions. The developed control system promotes the adoption of RCCI combustion in commercial marine engines.

Fire behavior of Automated Rack Supported Warehouses

The fire behavior of the automated rack-supported warehouse (ARSW) is a topic of great interest both for the scientific community and for the manufacturers of industrial racks. However, their behavior in case of fire of is still poorly known. ARSW is a particular type of steel racks that combine the structural efficiency of steel construction with automated machines for handling stored products. The paper investigates the fire scenario and the collapse mechanism of a typical ARSW by considering a fire model that allows vertical and horizontal propagation, starting from a localized fire, evaluated, and validated against experimental results. The study comprises two fundamental phases: fire simulation using a multi-zone model and investigation of the structural elements collapse through finite element structural analysis. An iterative procedure is proposed to correctly analyze the progressive mechanism of collapse by carrying out several subsequent implicit analyses with SAFIR software.

Изучение температуры гетерогенного пламени

Flames of heterogeneous condensed systems have sharp brightness inhomogeneities and their radiation is described using a multizone flame model. Each flame zone, which has its own level of brightness and, accordingly, temperature, makes a certain contribution to the total radiation of the flame. A wide-spectrum video camera with a large volume of CCD matrix served as a radiation receiver. A set of optical filters allows to register radiation in a narrower spectral range. The digitized flame image was processed by developed software in order to highlight zones with certain optical characteristics in a flame image. By comparing the brightness of flame zones with the brightness of reference light sources, the temperature of the flame zones and the radiation intensity of in different spectral ranges were determined. Single receivers register radiation from all flame zones and produce an average signal. Using flame radiation modeling methods, it has been shown that the single receiver signal, the level of which determines the flame temperature, depends on the number of zones.

Quantifying the impact of Covid-19 on the energy consumption in the low-income housing in Greater London

Covid-19 has caused great challenges to the energy sector, particularly in residential buildings with low-income households. This study investigates the impact of the confinement measures due to the Covid-19 outbreak on the energy demand of seven residential archetype buildings in Greater London. Three levels of confinement for occupant schedules are proposed and compared with the base case before Covid-19. The archetypes, their boundary conditions, and input parameters are set up according to statistics from English Housing Survey (EHS) sample data for low-income housing. The base case scenario (normal life without confinement measures) is validated against the measured data energy consumption from the National Energy Efficiency Data-Framework (NEED) statistics. The results show that electricity consumption is significantly lower than that for heating and hot water for all the archetypes. By comparing the base case scenario with the full Covid-19 lockdown scenario, the results indicate that heating and hot water consumption (kWh) for all the residential archetypes increases, on average, by 10%, and total electricity demand (kWh) increases by 13%. The study highlights the importance of introducing detailed occupancy profiles in multi-zone building energy simulation models during a pandemic that leads to a greater shift towards home working, which may increase the risk of fuel poverty in low-income housing.

Building Simulation Software for Indoor Air Quality Research: A Review

In this digital era, information technology really helps the process of designing and designing a more efficient, durable, high-performance building. After the pandemic, indoor air quality (IAQ) becomes an important issue since human spend most of the time indoor, which can impact their well-being in the long term. Ventilation is considered as one of the effective strategies in order to control IAQ. However, airflow and pollutant transport are a complex mechanism, therefore it is hard to understand only by experimental method. Advance information technology nowadays can help predict the building air quality from the early design stage. This paper aims to discuss various building simulation models and the popular software used. The basic principles of three models, multizone, zonal, and computational fluid dynamic (CFD) models are explained, following with their advantages and limitation. By comparing the simulation ability, accuracy, computational cost, simulation time, user skill requirement, and visual user interface, architect and researcher can choose the right simulation model according to their needs, in designing building which emit less pollutant and provide enough ventilation for contaminants discharge.

NLTE spectra of kilonovae

ABSTRACT The electromagnetic transient following a binary neutron star merger is known as a kilonova (KN). Owing to rapid expansion velocities and small ejecta masses, KNe rapidly transition into the non-local thermodynamic equilibrium (NLTE) regime. In this study, we present synthetic NLTE spectra of KNe from 5 to 20 d after merger using the sumo spectral synthesis code. We study three homogeneous composition, 1D multizone models with characteristic electron fractions of Ye ∼ 0.35, 0.25, and 0.15. We find that emission features in the spectra tend to emerge in windows of reduced line blocking, as the ejecta are still only partially transparent even at 20 d. For the Ye ∼ 0.35 (lanthanide-free) ejecta, we find that the neutral and singly ionized species of Rb, Sr, Y, and Zr dominate the spectra, all with good potential for identification. We directly test and confirm an impact of Sr on the 10 000 Å spectral region in lanthanide-free ejecta, but also see that its signatures may be complex. We suggest the Rb i$\rm {5p^{1}}$–$\rm {5s^{1}}$ 7900 Å transition as a candidate for the λ0 ∼ 7500–7900 Å P-Cygni feature in AT2017gfo. For the Ye ∼ 0.25 and 0.15 compositions, lanthanides are dominant in the spectral formation, in particular Nd, Sm, and Dy. We identify key processes in KN spectral formation, notably that scattering and fluorescence play important roles even up to 20 d after merger, implying that the KN ejecta are not yet optically thin at this time.

Kinetic modeling of ion chemistry in diesel engines using a novel reduced ionic chemical mechanism

BackgroundModeling ion current in combustion processes based on chemical kinetics mechanisms, results in more accurately calculating of the temperature and pressure of the combustion chamber. The use of ionic mechanisms also estimates the output pollutants of the combustion chamber with higher accuracy. MethodsThe aim of the current study is modelling of ion chemistry during diesel combustion. To achieve this goal, a multi-zone thermodynamic model was used to model the diesel engines performance. The chemistry of the combustion is simulated based on a kinetic mechanism with 327 reactions and 75 species. To reduce this mechanism, the progress rates of the reactions were calculated at the start of combustion, end of combustion, and CAD50 for three different cases, and essential reactions were detected. The reduced mechanism includes 44 species and 92 reactions. At the next step, ions and ion-based reactions were added to the reduced mechanism, and the reduced ionic mechanism was developed with 98 reactions and 49 species Significant FindingsThe results show that CH formation during the combustion process is the source of ion production inside the combustion chamber. The reduced ionic mechanism could accurately predict in-cylinder pressure, heat release rate, the start of combustion, and the location of 50% cumulative heat release. The highest error in prediction of CAD50 is less than 0.1%.

Thermodynamic analysis of the effect of initial ortho-hydrogen concentration on thermal behaviors for liquid hydrogen tanks

Due to the extra evaporation loss caused by the ortho-para hydrogen conversion (OPHC) during the storage and transportation of liquid hydrogen (LH2), the initial concentration of ortho-hydrogen (o-H2) plays an important role in the large-scale safe operation and utilization of LH2. However, there are very limited studies focusing on clarifying the impact of the OPHC on thermal behaviors of LH2 tanks. In light of this, this paper establishes and develops an extended thermal multi-zone model that couples the OPHC process with the mass and energy conservation equations of the ullage and liquid for an LH2 tank. With the help of the model, a thermodynamic analysis of the pressurization rate is performed to obtain the dominant parameter that evaluates the effect of the initial o-H2 concentration on the pressure build-up process. The results indicate that the interfacial mass transfer rate caused by the OPHC is the dominant parameter accounting for more than 90% of the effect of all parameters on the pressurization rate during a 10-day process with an initial liquid fill ratio of 90% and a heat leakage of 40 W. Additionally, the effect of the initial o-H2 concentration on the optimal liquid fill ratio is discussed in this paper. The results indicate that when the initial o-H2 concentration changes from 0.2% to 10%, the optimal liquid fill ratio decreases from 82.5% to 74%. The present work provides theoretical support and guidance for controlling the o-H2 concentration to realize the long-term and high-efficiency storage of LH2.

Multi-Zone Infection Risk Assessment Model of Airborne Virus Transmission on a Cruise Ship Using CONTAM

Since the onset of the pandemic, the cruise industry has faced substantial challenges, experiencing an 81% year-on-year decline in 2020. Notably, China’s cruise industry has remained shuttered for nearly two years. The conventional epidemiological investigations relying on human memory have proven inadequate in regard to swiftly and reliably identifying high-risk populations, thus leading to excessive pandemic prevention or other inappropriate measures. Furthermore, current research endeavors have not adequately addressed the critical issues of isolation location selection and the estimation of isolation scale within multi-zone indoor environments. Therefore, how to control the epidemic with minimal impact on the public has become an urgent problem. To solve the problems mentioned above, a multi-zone infection risk assessment model of airborne virus transmission was proposed to rapidly qualify the risk of infection, identify the high-risk population, and provide guidance. The model can be divided into two parts, including a multi-zone airflow model and a risk assessment model based on the Wells–Riley model. A large in-service ro-ro passenger ship already in service was used for the application of the proposed method. The results show that the number of isolated rooms shall be at least 5% of the occupancy and the isolation location can be chosen through the multi-zone infection risk assessment model. This paper provides insights into risk assessment to mitigate the spread of epidemics on a large cruise ship, and the method can be easily applied to all kinds of multi-zone indoor environments.

Online model-based predictive control with smart thermostats: application to an experimental house in Québec

This paper tests the impact of model resolution and structure on the performance of Model Predictive Control (MPC) implementation in an unoccupied research house in Québec equipped with smart thermostats. Two low-order models and a high-order multi-zone model were calibrated with measured data, with the structure of the multi-zone model being generated automatically during the calibration procedure. The three models were used to apply real-time MPC to an experimental house in Québec using the established dynamic tariffs for morning and evening peaks. MPC with any of the three models successfully preheated the house before the demand-response events, outperforming the reference reactive controller, reducing cost and thermal discomfort. The high-order multi-zone model performed the best, reducing average cost of electricity by 55% and high-price energy consumption by 71%, compared to the low-order models, which achieved cost reductions of 40% and 44% and energy consumption reductions of 48% and 54% respectively.

A multi-zone thermodynamic model for predicting LNG ageing in large cryogenic tanks

During the storage and transportation of liquefied natural gas (LNG), generation of boiloff gas (BOG) and change in the LNG composition, also known as LNG aging, are inevitable. Thus, a thermodynamic model that can accurately predict LNG aging during long-term operation is critical. This study presents a novel aging model, in which the LNG tank is divided into five zones: the vapor phase region, thermal stratification, bulk liquid region, boundary layer, and surrounding thermal insulation region. The heat and mass transport into different regions were calculated separately, and the thermal conductivity of the solid walls was considered as a function of temperature. Following model validation, simulations were performed for various thermal insulation conditions, ambient temperatures, and initial liquid compositions. From the results, the errors of the pressure, BOG rate and total heat flux could be approximated to 17, 7, and 14% respectively, for the previous models omitting the variation of thermal conductivity with temperature. As the initial methane fraction increased (i.e., N fraction decreases), the BOG rate decreased at the initial stage, while the BOG rate became less sensitive with the initial LNG composition as evaporation proceeded. Such an effect is determined by the variation in the latent heat of vaporization and total heat loss. This study can provide guidance for the design and operation of LNG storage tanks.

Planning ride-pooling services with detour restrictions for spatially heterogeneous demand: A multi-zone queuing network approach

This study presents a multi-zone queuing network model for steady-state ride-pooling operations that serve heterogeneous demand, and then builds upon this model to optimize the design of ride-pooling services. Spatial heterogeneity is addressed by partitioning the study region into a set of relatively homogeneous zones, and a set of criteria are imposed to avoid significant detours among matched passengers. A generalized multi-zone queuing network model is then developed to describe how vehicles’ states transition within each zone and across neighboring zones, and how passengers are served by idle or partially occupied vehicles. A large system of equations is constructed based on the queuing network model to analytically evaluate steady-state system performance. Then, we formulate a constrained nonlinear program to optimize the design of ride-pooling services, such as zone-level vehicle deployment, vehicle routing paths, and vehicle rebalancing operations. A customized solution approach is also proposed to decompose and solve the optimization problem. The proposed model and solution approach are applied to a hypothetical case and a real-world Chicago case study, so as to demonstrate their applicability and to draw insights. Agent-based simulations are also used to corroborate results from the proposed analytical model. These numerical examples not only reveal interesting insights on how ride-pooling services serve heterogeneous demand, but also highlight the importance of addressing demand heterogeneity when designing ride-pooling services.

First-principles-integrated Study of Blazar Synchrotron Radiation and Polarization Signatures from Magnetic Turbulence

Blazar emission is dominated by nonthermal radiation processes that are highly variable across the entire electromagnetic spectrum. Turbulence, which can be a major source of nonthermal particle acceleration, can widely exist in the blazar emission region. The Turbulent Extreme Multi-Zone (TEMZ) model has been used to describe turbulent radiation signatures. Recent particle-in-cell (PIC) simulations have also revealed the stochastic nature of the turbulent emission region and particle acceleration therein. However, radiation signatures have not been systematically studied via first-principles-integrated simulations. In this paper, we perform combined PIC and polarized radiative transfer simulations to study synchrotron emission from magnetic turbulence in the blazar emission region. We find that the multiwavelength flux and polarization are generally characterized by stochastic patterns. Specifically, the variability timescale and average polarization degree (PD) are governed by the correlation length of the turbulence. Interestingly, magnetic turbulence can result in polarization angle swings with arbitrary amplitudes and duration, in either direction, that are not associated with changes in flux or PD. Surprisingly, these swings, which are stochastic in nature, can appear either bumpy or smooth, although large-amplitude swings (>180°) are very rare, as expected. Our radiation and polarization signatures from first-principles-integrated simulations are consistent with the TEMZ model, except that in the latter, there is a weak correlation, with zero lag, between flux and degree of polarization.

High Quality Multi-Zone and 3D CFD Model of Combustion in Marine Diesel Engine Cylinder

Abstract The paper presents a 3D model of the processes taking place in the cylinder of a large 4-stroke marine engine. The model is based on CFD calculations performed on the moving mesh. The modelling range includes the full duty cycle (720° crankshaft position) and the complete geometry of the cylinder with inlet and exhaust ducts. The input data, boundary conditions and validation data were obtained by direct measurements on the real object. Fuel injection characteristics were obtained by Mie scattering measurements in a fixed-volume chamber. The modelling results have been validated in terms of the pressure characteristics of the engine’s cylinder within the entire range of its loads. The mean error did not exceed 1.42% for the maximum combustion pressure and 1.13% for the MIP (Mean Indicated Pressure). The model was also positively validated in terms of the O2 and NOx content of the exhaust gas. The mean error in this case was 1.2% for NOx fractions in the exhaust gas and 0.4% for O2 fractions. The complete model data has been made available in the research data repository on an open access basis.

Data reduction considerations for the burning velocity of spherical constant volume flames of R32 (CH2F2) with air

The present work explores data reduction techniques for the measurement of the laminar burning velocities of R32(CH2F2)-air mixtures using a constant volume combustion device, in which the pressure-time history is the only measured parameter. To allow clear assessment of the accuracy of the data reduction methods, the pressure-time histories used for analysis are synthetically generated via a detailed numerical simulation employing full kinetics and with and without an optically-thin radiation model. Various data reduction models are employed, including a two-zone model and two multi-zone models, and these are compared with the results from the burning velocity obtained from the output of the numerical simulation. The data reduction schemes are shown to be accurate if the same radiation model is employed in the data reduction as was used in the flame simulation to generate the pressure trace used for post-processing. If the incorrect radiation model is employed, however, the errors can be quite large. The effects of stretch, radiation, and different data post-processing methodologies are explored and the errors quantified. Stretch is shown to be important for the early stages and the selected data range that is used for extrapolation has a significant effect on the extrapolated burning velocity. However, with an appropriate choice of data considered for extrapolation, the prediction of the unstretched burning velocity can be quite accurate.

A Bayesian chemical evolution model of the DustPedia galaxy M74

ABSTRACT We introduce a new, multizone chemical evolution model of the DustPedia galaxy M74, calibrated by means of Markov Chain Monte Carlo methods. We take into account the observed stellar and gas density profiles and use Bayesian analysis to constrain two fundamental parameters characterizing the gas accretion and star formation time-scale, i.e. the infall time-scale τ and the SF efficiency ν, respectively, as a function of galactocentric radius R. Our analysis supports an infall time-scale increasing with R and a star formation efficiency decreasing with R, thus supporting an ‘Inside-Out’ formation for M74. For both τ and ν, we find a weaker radial dependence than in the Milky Way. We also investigate the dust content of M74, comparing the observed dust density profile with the results of our chemical evolution models. Various prescriptions have been considered for two key parameters, i.e. the typical dust accretion time-scale τ0 and the mass of gas cleared out of dust by a supernova remnant, Mclear, regulating the dust growth and destruction rate, respectively. Two models with a different current balance between destruction and accretion, i.e. with an equilibrium and a dominion of accretion over destruction, can equally reproduce the observed dust profile of M74. This outlines the degeneracy between these parameters in shaping the interstellar dust content in galaxies. Our methods will be extended to more DustPedia galaxies to shed more light on the relative roles of dust production and destruction.

A mathematical model for assessing transient airborne infection risks in a multi-zone hospital ward

Quantification of the parameters influencing airborne infection risks associated with indoor activities in different settings can help in understanding outbreak dynamics and the effective implementation of mitigation strategies. This is particularly important in hospitals, where the consequence of infections amongst vulnerable individuals can be significant. Despite the transient occupancy and inter-connected nature of hospital wards, the majority of airborne risk models assume steady-state conditions and well-mixed air in a single zone. We propose a multi-zone model with both a fixed and time-varying infectious person. We use an adapted version of the Wells–Riley model to estimate transient airborne virus concentration, and account for time-varying behaviour in the indoor setting. Through a coupling with a CONTAM airflow network model, we incorporate the effects of ventilation patterns on inter-zonal flow rates to represent likely airflow in a realistic hospital ward. We use this approach to explore the difference in predictions from transient versus steady-state models across several scenarios. Results suggest that a steady-state approach could lead to an overestimation of infection risk or underestimation of quanta emission, especially when the infectious person is only present for a short period of time. The difference between models is most apparent in poorly ventilated spaces, illustrating how risks can build over time when infectious occupant movement is more frequent than the removal rate due to ventilation. The model highlights the importance of considering transient factors when assessing infection risks to ensure that the most effective mitigation strategies are implemented to address long and short timescale risks.

Modelling the ingress and charge enhanced deposition behaviour of radioactive aerosols in dwellings

Radioactive aerosols of accidental origin can travel long distances once airborne and although dwellings can provide some shelter, ingressed radioactive aerosol has been shown to be injurious to human health. Modelling approaches have been widely used to study indoor aerosol behaviour, but such approaches have not to date considered the self-charging nature of radioactive aerosol and the consequent effect upon aerosol deposition. In this work, a multi-zone modeling tool is used to simulate indoor aerosol concentrations in the individual rooms of a bungalow and semi-detached dwelling, for three radioactive aerosol particles sizes (0.5, 1.0, 2.0 μm, with aerosol deposition enhancement due to particle charge), two plume types (5 h and 24 h), and a range of representative dwelling airflow conditions (low air flow LAF and high air flow HAF1), including mechanical extract ventilation (HAF2). When comparing the time series of aerosol concentrations in different rooms, lower concentrations of charged aerosol, relative to uncharged, were observed, suggesting charge-enhanced deposition, and this phenomena is more striking during a 24 h plume compared to 5 h plume, where the difference between the two is up to 50% in one of the zones of the dwelling. The concentration comparison of charged aerosols concentration between LAF and HAF1 cases also showed that during a 5 h plume, the aerosol concentration is twice as high for the HAF1 case. These simulation results demonstrate that the effect of charged-enhanced aerosol deposition should be considered when assessing the benefits of sheltering in a building in the event of a nuclear accident.