Plant Simulation Research Articles

Application of plant simulation software as a process improvement tool in automotive radio line

As empresas necessitam aprimorar seus processos para atender às demandas dos consumidores. Diante disso, a simulação computacional é uma ferramenta poderosa para a implementação de melhorias no processo, pois consiste na representação virtual de um sistema em diferentes cenários, auxiliando na tomada de decisões. Assim, neste estudo, foi empregado o programa de simulação Plant Simulation para determinar o tamanho ideal das WIPs de uma linha de montagem de rádios automotivos no distrito industrial de Manaus, levando em conta o princípio do Just In Time (JIT) de produzir somente o necessário. A simulação computacional foi realizada com os dados reais do processo de montagem, em que estes dados foram obtidos através da cronoanálise das estações de trabalho da linha de montagem e através da metodologia de Yamazumi para identificar as principais perdas do processo. Após o dimensionamento dos WIP’s por meio do software de simulação, foi feita a implementação na linha de montagem. Os resultados foram positivos, pois ocorreu a diminuição da ociosidade das máquinas do processo e, consequentemente, o aumento de 6% da capacidade produtiva da linha.

Design and Simulation of the Biodiesel Process Plant for Sustainable Fuel Production

The biodiesel production process is extensively studied in the literature, focusing on mechanisms, modeling, and economic aspects, yet plant design and fluid flow losses remain underexplored areas. The study addressed this gap by designing a biodiesel production plant, analyzing flow losses, and developing a pipe network and suitable pump models. In this study, an integration of biodiesel production plant design and simulation of continuous production of Calophyllum inophyllum biodiesel was investigated. Biodiesel production encompasses complex stages that involve systematic planning and system design. The goal of the plant design is to reduce the losses that occur during the conversion process, which can reduce the capital cost of the plant. A few assumptions were made when selecting biodiesel plant materials, such as pipes, pumps, fittings, and bends. These assumptions were based on considerations of the biodiesel fluid properties and pressure requirements. On the other hand, Aspen Plus was used to simulate the biodiesel production process. Calophyllum inophyllum was considered oil as the biodiesel feedstock and was inputted to the Aspen Plus as triglyceride composition. The simulation was carried out with rigorous kinetic reactions using the Non-Random Two-Liquid (NRTL) method to predict the liquid equilibrium in the reactor. Results revealed that the designed steel pipe meets safety requirements with a bursting pressure of 49.68MPa, capable of withstanding the maximum pressure of 4 bar and turbulent flow conditions. Additionally, the selected pump satisfies the required head and flow rate, ensuring efficient fluid movement. Moreover, simulation results closely matched experimental data, and 88% of biodiesel yield was recorded.

Application of standardized methods to evaluate the environmental safety of polyvinyl alcohol disposed of down the drain.

The purpose of this research was to use polyvinyl alcohol (PVOH) 18-88 as a case study to evaluate the environmental fate, ecotoxicity, and overall safety profile of water-soluble, nonmodified PVOH polymers used in detergent films. An OECD 303A Wastewater Treatment Plant Simulation Study was conducted with dissolved organic carbon as the analytical endpoint to evaluate the removal of PVOH 18-88 during wastewater treatment. During the plateau phase, high levels of removal due to biodegradation were observed (average 97.4 ± 7.1, range: 88%-116%). The OECD 303A study quantitatively verified that surface water is the dominant receiving compartment for PVOH 18-88 post wastewater treatment. Acute algae, invertebrate, and fish embryo (fish embryo acute toxicity test [FET]) ecotoxicity studies quanitified the 50% lethal/effect concentration (L/EC50) for PVOH 18-88. Due to the potential for the chorion to impact PVOH 18-88 bioavailability, both chorionated and dechorionated FET tests were conducted. L/EC50 > 1000 mg/L for FET (chorionated and dechorionated), invertebrate, and algae were observed. The Sustainable Futures (US) and REACH (EU) frameworks were used to evaluate environmental risk. For the US assessment, the Exposure and Fate Assessment Screening Tool was used to predict the single day lowest flow over a 10-year period (1Q10) surface water concentration and the seven consecutive days of lowest flow over a 10-year period (7Q10) surface water concentration and compared with acute and chronic concentrations of concern. For the EUassessment, the European Union System for the Evaluation of Substances was used to predict local and regional exposure concentrations and compared to the predicted no effect concentration. For both regulatory assessments, the exposure concentrations were >2 orders of magnitude below the effect concentrations. Integr Environ Assess Manag 2024;20:1693-1705. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Designing and simulation of a grid-connected solar plant in Mathura city region employing PVsyst

Existing electricity generation methods are ecologically unsustainable due to the industrial revolution's massive population growth and digitalization. The photovoltaic (PV) simulation tool is crucial for forecasting the solar system's energy output. The objective of this research is to simulate the feasibility of establishing a PV system isolated with batteries in Mathura, India, where the research is taking place to measure solar radiation and examine the technical and economic components of the PV system for generating domestic electrical energy requirements. The program has been implemented by PVsyst software. The amount of electricity that is added to the grid is 100.95 MWh. In the intended location, the Si-poly (polycrystalline silicon) PV system's typical performance ratio is 72.35%. From March to October, the most electrical energy was generated. The temperature of the solar field, which was 7.69%, was the primary cause of the losses observed in the research.

Solar-Assisted Carbon Capture Process Integrated with a Natural Gas Combined Cycle (NGCC) Power Plant—A Simulation-Based Study

In the realm of Natural Gas Combined Cycle (NGCC) power plants, it is crucial to prioritize the mitigation of CO2 emissions to ensure environmental sustainability. The integration of post-combustion carbon capture technologies plays a pivotal role in mitigating greenhouse gas emissions enhancing the NGCC’s environmental profile by minimizing its carbon footprint. This research paper presents a comprehensive investigation into the integration of solar thermal energy into the Besmaya Natural Gas Combined Cycle (NGCC) power plant, located in Baghdad, Iraq. Leveraging advanced process simulation and modeling techniques employing Aspen Plus software, the study aims to evaluate the performance and feasibility of augmenting the existing NGCC facility with solar assistance for post-carbon capture. The primary objective of this research is to conduct a thorough simulation of the Besmaya NGCC power plant under its current operational conditions, thereby establishing a baseline for subsequent analyses. Subsequently, a solar-assisted post-combustion capture (PCC) plant is simulated and seamlessly integrated into the existing power infrastructure. To accurately estimate solar thermal power potential at the Baghdad coordinates, the System Advisor Model (SAM) is employed. The integration of solar thermal energy into the NGCC power plant is meticulously examined, and the resulting hybrid system’s technical viability and performance metrics are rigorously evaluated. The paper contributes to the field by providing valuable insights into the technical feasibility and potential benefits of incorporating solar thermal energy into conventional natural gas power generation infrastructure, particularly in the context of the Besmaya NGCC plant in Baghdad. The power generation capacity of the plant was set at 750 MW. With this capacity, the annual CO2 generation was estimated at 2,119,318 tonnes/year which was reduced to 18,064 tonnes/year (a 99% reduction). The findings aim to inform future decisions in the pursuit of sustainable and efficient energy solutions, addressing both environmental concerns and energy security in the region.

Simulation and Modeling of Water Treatment Plant with GPS-X Software for Health and Water Quality

Background: Waterborne diseases are infectious in nature, significantly impacting global health related to water quality and disease prevalence globally. In this study, GPS-X was used to design and simulate water treatment plants to determine the effectiveness of different mechanisms in water treatment. Method: The GPS-X water treatment software was utilized to evaluate raw and treated water performance at the Al-Kadhmaya Water Treatment Plant. Three scenarios were designed to assess the impact of varying flow rates and water parameters such as pH, alkalinity, turbidity, total dissolved solids (TDS), and total suspended solids (TSS) on the plant's performance. Results: The evaluation of the operational performance of the water treatment plant revealed that the concentrations of all contaminants in the effluent water consistently met the established Iraqi and WHO standards across all scenarios. This indicated the effectiveness of the plant's treatment processes in producing safe drinking water. The findings of this study held significance for water authorities, decision-makers in Iraq, and national and international environmental agencies, providing valuable information for improving water treatment practices and ensuring compliance with water quality standards. Conclusion: The study demonstrated the effectiveness of the GPS-X water treatment software in assessing the performance of the Al-Kadhmaya Water Treatment Plant. The results highlighted the plant's ability to consistently meet water quality standards, underscoring the importance of robust water treatment processes. These findings contributed to the body of knowledge regarding water treatment plant design and operation, offering insights that can inform decision-making processes to enhance water quality and ensure public health.

Thermal hydrolysis pretreatment of wastewater biosolids: Modelling the impact of the aerobic sludge age

This study investigates the impact of thermal hydrolysis pretreatment (THP) on the characteristics of wastewater biosolids, methane production, anaerobic biodegradability, and recycled sidestream nitrogen loads, as a function of the sludge age of the activated sludge (AS) system through a series of BioWin simulations of 3 different process configurations at sludge ages of 5, 10, 15, 20, 30, and 60 d, with and without thermal hydrolysis. BioWin's anaerobic digester and thermal hydrolysis units were calibrated by adopting and identifying various kinetic and operational parameters from the available literature and through series of full-scale plant simulations. Thermal hydrolysis improved the hydrolysis rates of the biosolids by 181%. Improvements in anaerobic biodegradability, mainly due to the conversion of endogenous products, ranged from 14% to 67% at sludge ages of 5–15 d. At sludge ages of 20–60 d, anaerobic biodegradability improved by 59% to 186% depending on the process configuration. At sludge ages of 15–60 d, methane production was relatively stable and insensitive to the biosolids composition. Despite the increase in the recycled nitrogen load by 42% to 127%, it only constituted 13% of the influent nitrogen load. Effluent ammonia concentrations remained unchanged and effluent nitrates concentrations only increased by 1.4 to 2 mg N/L, maintaining effluent standards without additional sidestream treatment.

Estimating multivariate ecological variables at high spatial resolution using a cost‐effective matching algorithm

AbstractSimulation models are valuable tools for estimating ecosystem response to environmental conditions and are particularly relevant for investigating climate change impacts. However, because of high computational requirements, models are often applied over a coarse grid of points or for representative locations. Spatial interpolation of model output can be necessary to guide decision‐making, yet interpolation is not straightforward because the interpolated values must maintain the covariance structure among variables. We present methods for two key steps for utilizing limited simulations to generate detailed maps of multivariate and time series output. First, we present a method to select an optimal set of simulation sites that maximize the area represented for a given number of sites. Then, we introduce a multivariate matching approach to interpolate simulation results to detailed maps for the represented area. This approach links simulation output to environmentally analogous matched sites according to user‐defined criteria. We demonstrate the methods with case studies using output from (1) an individual‐based plant simulation model to illustrate site selection, and (2) an ecosystem water balance simulation model to illustrate interpolation. For the site selection case study, we identified 200 simulation sites that represented 96% of a large study area (1.12 × 106 km2) at a ~1‐km resolution. For the interpolation case study, we generated ~1‐km resolution maps across 4.38 × 106 km2 of drylands in North America from a 10 × 10 km grid of simulated sites. Estimates of interpolation errors using cross validation were low (<10% of the range of each variable). Our point selection and interpolation methods, which are available as an easy‐to‐use R package, provide a means of cost‐effectively generating detailed maps of expensive, complex simulation output (e.g., multivariate and time series) at scales relevant for local conservation planning. Our methods are flexible and allow the user to identify relevant matching criteria to balance interpolation uncertainty with areal coverage to enhance inference and decision‐making at management‐relevant scales across large areas.

Increasing the Production Capacity of Business Processes Using Plant Simulation

Increasing the Production Capacity of Business Processes Using Plant Simulation

Optimal operation of a natural gas sweetening plant

The most common method of removing acid gases from natural gas is through the use of solvent-based gas sweetening plants, which are energy-intensive. The present study aims to establish a plant-wide structure to operate natural gas sweetening plants optimally. Thus, a steady-state simulation of the Khangiran plant was carried out, and a 17% reduction in energy usage was achieved as a result of the optimization by the application of surrogate models. The self-optimizing method was applied to find the best set of controlled variables (CVs). There was found one unconstrained degree of freedom (DOF). The best CV for the remaining DOF was found to be the top stage temperature of the regenerator. Aspen Plus Dynamics was used to examine the performance of the proposed control structure utilizing simple traditional PIDs and compare it to modern feedback and feedforward MPCs.

HelioSoil: A Python Library for Heliostat Soiling Analysis and Cleaning Optimization

Soiling losses and their mitigation via cleaning operations represent important challenges for Solar Tower (ST) plants. Yet soiling losses are not well considered in existing CSP software, likely due to the lack of tools for soiling estimation and cleaning optimization. In this paper, a Python-based heliostat soiling library, called HelioSoil, is introduced which allows for the assessment of heliostats’ soiling state and the optimization of the solar field cleaning schedule to maximize plant profit. The library is freely available on GitHub under a LGPL license, which enables extensions via other Python APIs (e.g. CoPylot) and integration with other CSP plant simulation packages to consider soiling losses. This latter capability is demonstrated in this study through an LCOE assessment and cleaning optimization of a hypothetical Australian ST plant with SolarTherm. Hence, HelioSoil provides the CSP community with a package for soiling assessment and cleaning resource optimization, which can be integrated with available software for high-level, long-term simulations. HelioSoil facilitates the inclusion of soiling and cleaning costs in CSP economics and ultimately aim to de-risk the deployment of ST plants.

Simulation and Control of Solar Thermal Power Plants

In this paper, first the overall modeling approach for an optimized control of a hot-gas cycle for solar thermal power plants in the Modelica language is pointed out. The emphasis of the modeling work lies on the development of dynamic component models to be used in control systems. Depending on the control task, the discretization of the models has to be adapted. Main components of the hot-gas cycle are the solar thermal receiver and the storage system. The steam cycle is preliminarily only included as heat sink. Second, for control purposes a linear model-based controller (MPC) was implemented in Modelica based on an external state-of-the-art QP solver [2] linked to the Modelica model. The performance of the MPC is compared with a basic automation scheme based on classical PID controllers.

GrowSpace: A reinforcement learning environment for plant architecture

Plants adapt over time to their surrounding conditions. We argue that no current plant simulator addresses plant responses to an environmental stimulus over time through gamification and sequential decision making. We propose the GrowSpace simulator that is built within a reinforcement learning framework, providing a sandbox environment to test out hypotheses. GrowSpace currently focuses on the behavioral response of plants to light displacement, with the objective of controlling a plant’s shape by moving a light source. The back-end of the simulator is implemented using the Space Colonisation Algorithm. This simulator serves as a low-dimensional test bed to visualize plant growth and movement with respect to a light stimulus and to better understand a plant’s reactions to these conditions. GrowSpace provides an artificial modular environment that is simulated to the advancements of plant biological systems all while using a reinforcement learning framework. Tasks are crafted and tested with artificial intelligence algorithms to further understand the concept of plant growth control through light. We equally demonstrate that sequential control of plant branching is hard challenge for the plant science community as well as the reinforcement learning community.

Unleashing Manufacturing Potential: A Simulation-Based Journey Towards Optimal Efficiency

In the increasingly competitive landscape of manufacturing, companies are continuously striving to enhance their production processes, minimize expenses, and uphold exceptional quality standards. A valuable approach to achieving these objectives involves the utilization of plant simulation software which enables businesses to analyze, plan, and simulate their manufacturing operations, facilitating optimization and cost reduction while maintaining superior quality levels. This study aims to explore the application of plant simulation in a large company, with a focus on identifying areas for optimization and increased efficiency of the whole product lifecycle. The research will involve simulating a real-life manufacturing process, including both production and service kits, using simulation software. The performance of the simulated plant system will be analyzed to evaluate its effectiveness. By doing so, this study will contribute to the existing knowledge base of product lifecycle management and plant simulation and provide valuable insights to manufacturers seeking to enhance their production processes and achieve their business objectives. Furthermore, it will showcase the capabilities and accuracy of plant simulation technologies, equipping manufacturers with the necessary information to make informed decisions regarding future production goals and estimates.

Approaches to accounting for random events in the modeling of production processes of production and logistics systems of machine-building enterprises

The paper considers approaches to the analysis and prediction of the state of production and logistics systems of machine-building enterprises. The main groups of random events that occur during the operation of production and logistics systems and can have a significant impact on the implementation of the production program are systematized. Simulation modeling systems are analyzed: AnyLogic, Plant Simulation, PlantTwin. The functional capabilities of simulation modeling systems for setting random events are considered. A comparison of simulation modeling systems is carried out by the method of setting the distribution of a random variable and by the possibilities of accounting for random events.

Simulation of a steam generation plant useful in the Tequila production process employing different fuels as a novel strategy for environmental impact assessment

Tequila industry is in a continuous process to achieve a long-term economic, environmental, and social sustainability in the Agave-Tequila chain. To meet this challenge, several strategies have been proposed to improve the production process and reduce the environmental impact. In the present research work, the simulation of a steam generation plant with different fuels (heavy fuel oil, natural gas, and biogas) will be performed from a Tequila producer located in Valles region, Jalisco. The innovation of the research work focuses on the presentation of a new alternative for evaluating the environmental impact of the food industry focused on the process and its interaction with the environment. To calculate the environmental impacts associated with each of the proposed alternatives, a simulation of the industrial process (Production 50,000 L/day of Tequila) was carried out using CHEMCAD® simulation software and ALOHA® software. The simulation consisted in 6 steam generation boilers, which were represented by a Gibbs reactor in an adiabatic operation with an outlet temperature of 2032 °C, being fed with air and fuel. The outlet of the reactor was connected to a heat exchanger in which the combustion gases were in contact with a stream of water. The calculations were based on the generation of 12,000 kg/h of steam which are distributed to the extraction (17.07°%), hydrolysis (22.14°%) and distillation (60.79°%) stages for Tequila production process. From combustion, gases were quantified at the exit of the chimney. It is concluded that the use of natural gas is the most environmentally friendly option with gasses emission of 284.87 Ton/year of NO, 0.26 Ton/year of NO2, 358.98 Ton/year of CO, 11337.71 Ton/year of CO2, and 1.73 Ton/year of SO2. Finally, using as an environmental indicator the emissions of kg/L of CO2 coming from Tequila produced (heavy fuel oil 0.82, natural gas 0.62, and biogas 0.73), it is concluded that the change of fuel to natural gas represents a 24°% decrease in greenhouse effect emissions, presenting itself as an effective sustainability strategy to be applied in the Agave-Tequila production chain.

Thermodynamic and exergoeconomic operation optimization and simulation of steam generation solar power plant

Thermodynamic and exergoeconomic operation optimization and simulation of steam generation solar power plant

Modeling and Parameter Optimization of Plant Factory Production System Under Low-Carbon Constraints

Highlights A life cycle approach to modeling the carbon footprint of leafy vegetables. Determine the optimal design parameters through logical and mathematical relationship derivation. The simulation model of leaf vegetable production line was established. The optimal parameter scheme was determined by multifactorial simulation tests. Abstract. In recent years, a plant factory has gradually become a new model of facility agriculture, and the optimization problem of low-carbon design of production system in a plant factory has become more prominent. In the design of the production system, needs of high efficiency, high yield, and low carbon emission must be considered. In this study, the leafy vegetable factory is taken as the research object, and the carbon footprint calculation model of products is established based on the life cycle assessment method. Taking production capacity and carbon footprint as design indicators, the logical correlation and mathematical relationship between them and production line design parameters are analyzed layer by layer to determine the key design parameters. The leafy vegetable production line is modeled by plant simulation software, and multifactor simulation experiments are set up to explore the influence of key design parameters on design indexes to guide the optimal decision of parameter design scheme. The new design scheme increases the productivity of the plant factory by 35.40%, reduces the carbon footprint of leafy vegetables by 15.54%, and solves the problem that leafy vegetables at the bottom of the planting frame in the original plant factory grow poorly because of insufficient light. Keywords: Carbon footprint, Life cycle assessment, Plant factory, Product system, Production line modeling.

Application of Virtual Production to Upgrade Industrial Production Units

Our research work involves the study, analysis and modernisation of the production line of a company that has been operating with traditional systems for a long time with unchanged principles. The paper highlights the use of virtual production as a tool for modernising the company's production processes, providing a comprehensive understanding of its characteristics, advantages and positive impact on process development. The scientific article, after an overview of a selected real production process, describes the steps to build a digital twin for the implementation of virtual manufacturing. It explains in detail the different features and the results obtained in the Tecnomatix Plant Simulation modelling environment used to build the model. After evaluating the simulation, the paper examines the current state of the real process and its overall tool efficiency, and based on the conclusions drawn, it presents a way forward for the development of the production line and the possibilities for further research.

Modeling, Integration and Simulation of the Photovoltaic Power Plant Considering LVRT Capability and Transient Voltage Stability

This paper investigates how high photovoltaic energy penetration impacts dynamic performance and voltage regulation of the modified IEEE-9 bus grid. The transmission power system was modeled and simulated using PSCAD-EMTDC software to conduct the study. Load flow analysis is implemented to explore the power system’s capability to incorporate the desired photovoltaic power. Moreover, the study is based on time response simulations to grid disturbances. The supply and control of reactive power from solar power generation plants are becoming critical issues to study because they can facilitate the integration of PV in power grids under different operating conditions. Network-related faults like a PV solar power plant event outage, a three-phase short-circuit at a conventional bus, and a voltage dip at the PV solar power plant have been considered. The results will help identify the protective devices and strategies needed to maintain the stability and reliability of the system operation and transient analysis of the network under external power network fault and recovery operation. Thus, it has practical significance for real utility studies. Moreover, this comprehensive study will be a valuable guide for assessing and improving the grid’s performance under the study of any other grids, which also gives the vast potential and need for solar energy penetration into the grid systems.