Dynamic Mass Balance Research Articles

Contemporary and Future Secondary Copper Reserves of Southeast Asian Countries

This study employed dynamic material flow analysis (MFA) and mass balance principles to examine copper flows in Indonesia, Malaysia, the Philippines, Thailand, and Vietnam from 1960 to 2020, with projections extending to 2050 using five shared socioeconomic pathway (SSP) scenarios. We applied the secondary resources classification framework to assess secondary copper resources and their recoverability in these countries. The results indicated that total copper stocks across these countries would continue to rise, with Indonesia’s copper stock projected to reach around 5000–12,000 kt by 2050, the highest among the five nations. In 2022, Malaysia had the highest per capita copper stock at 100 kg/person, although all countries were expected to remain below the per capita stock levels seen in major copper-consuming developed countries by 2050. Copper demand was projected to increase by 118–238 kt annually from 2023 to 2050, leading to a significant rise in end-of-life copper scrap. By 2050, secondary copper reserves in Indonesia were estimated to reach 4096 kt, with similar growth trends observed in other countries (3898 kt in Thailand, 3290 kt in Vietnam, 3096 kt in Malaysia, and 2564 kt in the Philippines). This highlights both the potential for resource recovery and the need for improved waste management. If recycling rates increase to 80–90%, secondary reserves could meet up to 42–65% of the copper demand in 2050. However, current recycling rates remain well below this potential, underscoring the urgent need for better waste management systems. This study emphasizes the balance between economic development and resource sustainability, offering critical insights for policymakers to improve recycling efficiency and reduce reliance on primary copper sources.

Five definitions of adsorption and their relevance to the formulation of dynamic mass balances in gas adsorption columns

Numerous dynamic mass balances in the literature that describe the adsorption of gases in a column are written in terms of actual or absolute adsorption, while unwittingly and incorrectly utilizing excess adsorption isotherms. Perhaps this is because the actual and absolute adsorption isotherms cannot be experimentally measured nor predicted without making uncertain assumptions. The objective here was to derive unambiguous relationships between actual, absolute, excess, net and column amounts adsorbed that provide a straightforward understanding of the subtle differences between these quantities and that provide a simple means for incorporating them into dynamic mass balances. For this purpose, the actual, absolute, excess, net and column amounts adsorbed (loadings) were clearly defined, along with various volumes, porosities and densities that exist inside and outside an adsorbent contained in a column with a gaseous adsorbate. These adsorption definitions and quantities were used to derive four interconversion relationships for each type of adsorption in terms of the actual loading. The resulting expressions, based on intensive properties, can be used to relate any adsorption definition to any other adsorption definition. These relationships were also used to derive five dynamic mass balances, one for each type of adsorption. The similarities and differences in the terms between each of these five dynamic mass balances were discussed, along with their applicability to real world problems. In some cases at low pressure where the isotherms do not differ appreciably, it may be approximately correct to use excess or net adsorption isotherms in a dynamic mass balance written in terms of actual or absolute adsorption. However, the extent of the incorrectness is unknown due to mass transfer effects. So, it is recommended to use the dynamic mass balance with its specific type of adsorption, most likely excess adsorption. Then, when certain assumptions are made about the adsorbing and non-adsorbing void fractions, these expressions can be readily used in adsorption process simulation.

PID Controller Design for an E. coli Fed-Batch Fermentation Process System Using Chaotic Electromagnetic Field Optimization

This paper presents an optimal tuning of a proportional integral differential (PID) controller used to maintain glucose concentration at a desired set point. The PID controller synthesizes an appropriate feed rate profile for an E. coli fed-batch cultivation process. Mathematical models are developed based on dynamic mass balance equations for biomass, substrate, and product concentration of the E. coli BL21(DE3)pPhyt109 fed-batch cultivation for bacterial phytase extracellular production. For model parameter identification and PID tuning, a hybrid metaheuristic technique—chaotic electromagnetic field optimization (CEFO)—is proposed. In the hybridization, a chaotic map is used for the generation of a new electromagnetic particle instead of the electromagnetic field optimization (EFO) search strategy. The CEFO combines the exploitation capability of the EFO algorithm and the exploration power of ten different chaotic maps. The comparison of the results with classical EFO shows the superior behaviour of the designed CEFO. An improvement of 30% of the objective function is achieved by applying CEFO. Based on the obtained mathematical models, 10 PID controllers are tuned. The simulation experiments show that the designed controllers are robust, resulting in a good control system performance. The closed-loop transient responses for the corresponding controllers are similar to the estimated models. The settling time of the control system based on the third PID controller for all estimated models is approximately 9 min and the overshoot is approximately 15%. The proposed CEFO algorithm can be considered an effective methodology for mathematical modelling and achievement of high quality and better performance of the designed closed-loop system for cultivation processes.

Ozone Chemistry on Greasy Glass Surfaces Affects the Levels of Volatile Organic Compounds in Indoor Environments.

The chemistry of ozone (O3) on indoor surfaces leads to secondary pollution, aggravating the air quality in indoor environments. Here, we assess the heterogeneous chemistry of gaseous O3 with glass plates after being 1 month in two different kitchens where Chinese and Western styles of cooking were applied, respectively. The uptake coefficients of O3 on the authentic glass plates were measured in the dark and under UV light irradiation typical for indoor environments (320 nm < λ < 400 nm) at different relative humidities. The gas-phase product compounds formed upon reactions of O3 with the glass plates were evaluated in real time by a proton-transfer-reaction quadrupole-interface time-of-flight mass spectrometer. We observed typical aldehydes formed by the O3 reactions with the unsaturated fatty acid constituents of cooking oils. The formation of decanal, 6-methyl-5-hepten-2-one (6-MHO), and 4-oxopentanal (4-OPA) was also observed. The employed dynamic mass balance model shows that the estimated mixing ratios of hexanal, octanal, nonanal, decanal, undecanal, 6-MHO, and 4-OPA due to O3 chemistry with authentic grime-coated kitchen glass surfaces are higher in the kitchen where Chinese food was cooked compared to that where Western food was cooked. These results show that O3 chemistry on greasy glass surfaces leads to enhanced VOC levels in indoor environments.

Cadmium accumulation in soil resulting from application of biogas digestate and wood ash – Mass balance modelling

This study investigates the impact of substituting conventional NPK fertilizer with wood ash and biogas digestates at an agricultural field site in southwest Sweden. A three-year field experiment, comprising a crop rotation cycle of spring wheat, winter wheat, and oats, was conducted. The obtained results were employed to establish a dynamic mass balance model for the A horizon of the soil at the site. The Cd leaching term in the model was estimated using the Stockholm Humic model (SHM), which was recalibrated to accommodate low Cd concentrations by incorporating Cd complexation to thiol sites. The findings indicate that treatments receiving NPK fertilizer and biogas digestates experienced a net Cd loss, whereas treatments with wood ash demonstrated net Cd accumulation, attributed to its higher Cd content. Harvest yields were highest in the NPK treatment, and lower in two of the wood ash treatments, likely due to lower nitrogen additions in the latter. Cd offtake mirrored this trend, with the highest values in the NPK treatments and the lowest in the wood ash treatments, potentially also influenced by a pH difference of 0.2 units during the last year of the experiment. Geochemical modelling showed that Cd leaching is highly dependent on pH and that geochemically active soil Cd in the A horizon may have doubled between 1950 and 2002, due to elevated atmospheric deposition and fertilizer Cd during this period. Despite significant reductions in anthropogenic Cd fluxes since 2002, soil Cd has only decreased by 4%, showing the slow response of the soil pool to flux changes. Attaining a new steady-state after alterations in input fluxes will require hundreds of years. These results carry significance for determining sustainable application rates for recycled nutrient sources and underscore the crucial role of pH-dependent Cd sorption for Cd leaching.

Influence of shunt currents in industrial-scale alkaline water electrolyzer plants

The aim of this paper is to analyze through simulation how the energy efficiency of a single electrolysis stack at various loads is affected by shunt currents and to determine the energy-optimal load distribution between lines in a multiline electrolysis system under various magnitudes of shunt current losses. A dynamic energy and mass balance model of an industrial 3MW, 16bar alkaline water electrolyzer (AWE) process was developed using MATLAB. The optimization goal is to determine the power supply for each AWE line so that it can meet any hydrogen demand while minimizing the global specific energy consumption (SEC). The Particle Swarm Optimization (PSO) algorithm is used to minimize the objective function. According to the results of the single stack investigation, shunt current reduction could significantly improve the energy efficiency of partial-load operation. In addition, the optimization study revealed that whenever two or more lines are required to run in order to satisfy the hydrogen demand, the global SEC is minimized when the lines operate at equal loads.

CO2 dynamic mass balance of low permeability reservoir based on “four regions”

AbstractIn order to limit the increase in global average temperature to 1.5°C, it is necessary to reduce carbon dioxide (CO2) emissions by 45% by 2030. CO2 capture, utilization and storage (CCUS) is one of the effective ways to reduce CO2 emissions. Geological storage of CO2 provides a solution with the lowest economic cost and the fastest effect for reducing CO2 emissions. This article proposes a CO2 storage regional division method based on the characteristics of low‐permeability reservoirs in the Yanchang W oilfield in China. The storage space is divided into four regions: gas phase region, two‐phase or near‐miscible region, diffusion region, and oil phase region. As the displacement progresses, the volume of the gas phase region and the two‐phase or near‐miscible region gradually increases; the volume of the diffusion region first increases and then decreases. By calculating the storage capacity of each region separately, the total storage capacity is finally calculated. The impact of different pressures and injection rates on dynamic CO2 storage capacity was evaluated. The results show that pressure and injection rate are positively correlated with total storage capacity. When CO2 miscible conditions are reached, the increase in total storage capacity will significantly decrease. © 2024 Society of Chemical Industry and John Wiley &amp; Sons, Ltd.

Where does all the phosphorus go? Mass balance modelling of phosphorus in the Swedish long-term soil fertility experiments

To gain insights into phosphorus (P) dynamics in soils and the ability to predict soil responses to varying fertilizer inputs, mass balance models prove to be valuable tools. In this study, a new dynamic mass balance model, PBalD8, was used to describe the change in extracted P in the A horizon of soils subjected to diverse fertilizer treatments over a period of 50 to 60 years in five soil fertility experiments. The model employed a Freundlich equation to describe soil-solution partitioning of P and assumed that acid-lactate-extractable P represented a labile pool of P in instant equilibrium with soil solution P. Additionally, oxalate-extractable inorganic P was presumed to comprise the sum of the labile and stable pools of P, with mass flux to and from the latter described by Fick’s first law. The model was evaluated using results from extractions and P K-edge XANES spectroscopy. Notably, organic P, as revealed by P K-edge XANES, did not substantially contribute to long-term changes in soil P content and was therefore excluded from consideration. In general, the model offered reasonable fits to the extracted P concentrations. However, for the P-depleted treatments, a prerequisite was that the P removal through harvest was lower compared to measurements. Conversely, in three of the soils, the modelled fertilizer inputs needed to be reduced to 70 % to 85 % of the known additions. These discrepancies may be attributed to the involvement of deeper soil horizons, including deep crop uptake and mixing with lower soil layers, although other factors such as lateral dispersion and inaccuracies in estimating applied fertilizers cannot be discounted. These results underscore the necessity of gaining a more comprehensive understanding of how deeper soil horizons influence P mass balances in agricultural soils. In one of the soils, Fjärdingslöv, P K-edge XANES results demonstrated the formation of calcium phosphate over time in the highest fertilization treatment, consistent with the model. Additionally, in two soils, Kungsängen and the P-depleted Vreta Kloster soil, the model predicted a significant contribution from mineral weathering. However, the PBalD8 model also projected higher P leaching rates than those observed, suggesting that the model may not fully capture this P output term.

Online evaluation of the boiler energy efficiency associated with the soot blowing in coal‐fired power plants

AbstractSoot blowing is a common practice in coal‐fired power plants to ensure high energy conversion rate. The period of the conventional soot blowing is usually fixed, without the consideration of the load change and feeding coal switching. For the purpose of the soot blowing optimization, an approach to quantitatively evaluate the performance of soot blowing operations is proposed. Different heat exchangers' thermal resistances are calculated based on dynamic mass and energy balance to monitor their ash fouling deposition, and then, the boiler energy efficiency is predicted, adopting the rolling extreme tree boosting algorithm, and finally, the efficiencies with and without soot blowing are computed separately. With the data collected from a 350 MW ultra‐supercritical unit, pseudo‐online simulations are performed. The results show that even if the energy efficiency of the unit has exceeded 94%, a full‐process soot blowing may further increase the efficiency in some extent. For those subcritical units, the benefits should be higher.

Assessing pathways of heavy metal accumulation in aquaculture shrimp and their introductions into the pond environment based on a dynamic model and mass balance principle

The impact of heavy metals (HMs) on the quality of aquaculture products has attracted worldwide attention. Since Litopenaeus vannamei is a popular aquaculture product among consumers worldwide, it is of great importance to guarantee its dietary safety. An in-situ monitoring program lasting for three months in a typical Litopenaeus vannamei farm found that Pb (100 %) and Cr (86 %) in the adult shrimp were higher than the safety guidelines. In the meantime, Cu (100 %), Cd (100 %) in the water and Cr (40 %) in the feed exceeded the corresponding thresholds. Therefore, quantification of different exposure pathways of shrimp and contamination origins in pond is valuable to improve the dietary safety of the shrimp. Based on Optimal Modeling for Ecotoxicological Applications (OMEGA), Cu was primarily from the ingestion of feed, accounting for 67 % of bioaccumulation, while Cd, Pb and Cr primarily entered shrimp through the adsorption from overlying water (53 % for Cd and 78 % for Pb) and porewater (66 % for Cr), respectively. The HMs in the pond water were further tracked based on a mass balance analysis. The main source of Cu in the aquaculture environment was feed, being responsible for 37 % of the total input. Pb, Cd and Cr were primarily from the inlet water with contributions of 84 %, 54 % and 52 %, respectively. In summary, the proportions of different exposure pathways and origins of HMs in pond-cultured shrimp and its living environment varied widely. To keep end-consumers eating healthily, species specific treatment is required. Feed should be regulated more for Cu. Aimed pretreatments for Pb and Cd in influent water are needed and an additional immobilization for Cr in sediment porewater should be investigated. After implementation of these treatments, the food quality improvement could be further quantified based on our prediction model.

Global oceanic anoxia linked with the Capitanian (Middle Permian) marine mass extinction

The timing and causation of the Capitanian (late Middle Permian) biocrisis remain controversial. Here, a detailed uranium-isotopic (δ238U) profile was generated for the mid-Capitanian to lower Wuchiapingian of the Penglaitan section (the Guadalupian/Lopingian Permian global stratotype) in South China for the purpose of investigating relationships between the biocrisis and coeval oceanic anoxic events (OAEs). Negative δ238U excursions indicate two distinct OAEs, a mid-Capitanian (OAE-C1) and an end-Capitanian (OAE-C2) event. Mass balance modeling shows that the anoxic sink of uranium (Fanox; i.e., the fraction of the total U burial flux) and anoxic seafloor area (Farea; i.e., the fraction of total seafloor area) increased during each OAE. A dynamic mass balance model yields increases of Fanox from <30% to >60% and Farea from ∼1% to ∼4-7% during each OAE. These two OAEs coincided with two extinction episodes during the Capitanian biocrisis, supporting a causal relationship between oceanic anoxia and mass extinction during the Middle Permian. The most likely driver of middle to late Capitanian global warming and oceanic anoxia was episodic magmatism of the Emeishan Large Igneous Province.

A chaos-based adaptive equilibrium optimizer algorithm for solving global optimization problems.

The equilibrium optimizer (EO) algorithm is a newly developed physics-based optimization algorithm, which inspired by a mixed dynamic mass balance equation on a controlled fixed volume. The EO algorithm has a number of strengths, such as simple structure, easy implementation, few parameters and its effectiveness has been demonstrated on numerical optimization problems. However, the canonical EO still presents some drawbacks, such as poor balance between exploration and exploitation operation, tendency to get stuck in local optima and low convergence accuracy. To tackle these limitations, this paper proposes a new EO-based approach with an adaptive gbest-guided search mechanism and a chaos mechanism (called a chaos-based adaptive equilibrium optimizer algorithm (ACEO)). Firstly, an adaptive gbest-guided mechanism is injected to enrich the population diversity and expand the search range. Next, the chaos mechanism is incorporated to enable the algorithm to escape from the local optima. The effectiveness of the developed ACEO is demonstrated on 23 classical benchmark functions, and compared with the canonical EO, EO variants and other frontier metaheuristic approaches. The experimental results reveal that the developed ACEO method remarkably outperforms the canonical EO and other competitors. In addition, ACEO is implemented to solve a mobile robot path planning (MRPP) task, and compared with other typical metaheuristic techniques. The comparison indicates that ACEO beats its competitors, and the ACEO algorithm can provide high-quality feasible solutions for MRPP.

Nonlinear programming reformulation of dynamic flux balance analysis models

Dynamic flux balance analysis (dFBA) models are very popular in systems biology because of the many possible applications. dFBA consists of dynamic mass balance equations that describe the concentration of external metabolites and an optimization model to compute the internal flux distribution of the cell. Here, we applied a nonlinear programming formulation for solving dFBA models. The ODE system is discretized using the orthogonal collocation technique and the optimization problem is replaced by its first-order optimality conditions. In addition, an adaptive mesh scheme is applied to improve performance by efficiently handling changes in the active set of constraints. This formulation ensures total differentiability of the model, which can be solved by large-scale solvers and take advantage of automatic differentiation packages. The new approach presents results equivalent to state-of-the-art methods and outperforms them in dynamic optimization problems by avoiding calling an external solver to handle the embedded optimization model.

Opposition-based learning equilibrium optimizer with Levy flight and evolutionary population dynamics for high-dimensional global optimization problems

The equilibrium optimizer (EO) is a recently proposed physics-based metaheuristic algorithm inspired by the dynamic mass balance on a control volume. However, EO may encounter local convergence and low accuracy when solving high-dimensional optimization problems. In this work, we propose the opposition-based learning EO algorithm with the Levy flight and the evolutionary population dynamics for high-dimensional global optimization problems, called EOOBLE. Firstly, the opposition-based learning strategy is embedded into the initialization and updating process of EO. Then, the Levy flight strategy is used to improve the exploration ability of EO in the updating mechanism. Moreover, the strategy of evolutionary population dynamics is used in the proposed algorithm to avoid falling into the local optimum. The performance of the proposed algorithm is tested by 25 benchmark functions with dimensions from 100 to 5000, and is compared with 8 state-of-the-art metaheuristic algorithms. The statistical results indicate that the proposed algorithm has better convergence capacity than the compared algorithms. Besides, the proposed algorithm is also compared with different variants of EO, which outperforms the original EO and variants of EO with one or two operators. Therefore, the EOOBLE is a competitive algorithm in solving high-dimensional global optimization problems. Finally, a high-dimensional engineering design problem demonstrates the effectiveness of the EOOBLE.

Verification of TRANSPORT Simulation Environment coupling with PHREEQC for reactive transport modelling

Abstract. Many types of geologic subsurface utilisation are associated with fluid and heat flow as well as simultaneously occurring chemical reactions. For that reason, reactive transport models are required to understand and reproduce the governing processes. In this regard, reactive transport codes must be highly flexible to cover a wide range of applications, while being applicable by users without extensive programming skills at the same time. In this context, we present an extension of the Open Source and Open Access TRANSPORT Simulation Environment, which has been coupled with the geochemical reaction module PHREEQC, and thus provides multiple new features that make it applicable to complex reactive transport problems in various geoscientific fields. Code readability is ensured by the applied high-level programming language Python which is relatively easy to learn compared to low-level programming languages such as C, C++ and FORTRAN. Thus, also users with limited software development knowledge can benefit from the presented simulation environment due to the low entry-level programming skill requirements. In the present study, common geochemical benchmarks are used to verify the numerical code implementation. Currently, the coupled simulator can be used to investigate 3D single-phase fluid and heat flow as well as multicomponent solute transport in porous media. In addition to that, a wide range of equilibrium and nonequilibrium reactions can be considered. Chemical feedback on fluid flow is provided by adapting porosity and permeability of the porous media as well as fluid properties. Thereby, users are in full control of the underlying functions in terms of fluid and rock equations of state, coupled geochemical modules used for reactive transport, dynamic boundary conditions and mass balance calculations. Both, the solution of the system of partial differential equations and the PHREEQC module, can be easily parallelised to increase computational efficiency. The benchmarks used in the present study include density-driven flow as well as advective, diffusive and dispersive reactive transport of solutes. Furthermore, porosity and permeability changes caused by kinetically controlled dissolution-precipitation reactions are considered to verify the main features of our reactive transport code. In future, the code implementation can be used to quantify processes encountered in different types of subsurface utilisation, such as water resource management as well as geothermal energy production, as well as geological energy, CO2 and nuclear waste storage.

Using a dynamic mass balance model to predict fate and transport of PCBs in a polluted boreal lake in Sweden

In 2013, a screening survey including fish (European perch, Perca fluviatilis) from 20 locations in the Stockholm region of Sweden indicated exceptionally high levels of PCBs (>450 ng ΣPCB7/g ww) in Lake Oxundasjön. An extensive sampling program was launched to define the magnitude and area of impact of PCBs. Moreover, a dynamic mass balance model approach was applied to identify and quantify key transport processes and predict the long-term turnover of PCBs given various remediation scenarios.Based on the dating of sediment profiles, primary emissions of PCBs to Lake Oxundasjön have likely occurred from the end of the 1940s until 1980, reaching the lake via one of its tributaries. Presently, the main source of PCBs is diffusion from the lake sediments. From the lake outlet, >400 g ΣPCB7/yr are transported to Lake Mälaren (the third largest lake in Sweden), supplying drinking water for parts of the Stockholm area. Remediation actions are necessary to reduce the PCB levels in fish below today's marketing limits and environmental quality standards. With natural recovery, our results indicate that the PCB levels in non-migratory fish from Lake Oxundasjön will be elevated for decades to come.The mass of PCBs stored in the lake sediments was estimated, and to our knowledge, Lake Oxundasjön is the most heavily PCB contaminated lake in Sweden. The system constitutes a unique opportunity to test and develop a mathematical mass balance model for PCBs, with substantial data acquired from different aquatic matrices. The model presented in the paper is applicable for risk assessments of PCBs, and the results contribute to the general understanding of the transport and turnover dynamics of PCBs in aquatic ecosystems.

Dynamic Mass Balance Modeling for Chemical Distribution Over Time in In Vitro Systems With Repeated Dosing.

As toxicologists and risk assessors move away from animal testing and more toward using in vitro models and biological modeling, it is necessary to produce tools to quantify the chemical distribution within the in vitro environment prior to extrapolating in vitro concentrations to human equivalent doses. Although models predicting chemical distribution in vitro have been developed, very little has been done for repeated dosing scenarios, which are common in prolonged experiments where the medium needs to be refreshed. Failure to account for repeated dosing may lead to inaccurate estimations of exposure and introduce bias into subsequent in vitro to in vivo extrapolations. Our objectives were to develop a dynamic mass balance model for repeated dosing in in vitro systems; to evaluate model accuracy against experimental data; and to perform illustrative simulations to assess the impact of repeated doses on predicted cellular concentrations. A novel dynamic in vitro partitioning mass balance model (IV-MBM DP v1.0) was created based on the well-established fugacity approach. We parameterized and applied the dynamic mass balance model to single dose and repeat dosing scenarios, and evaluated the predicted medium and cellular concentrations against available empirical data. We also simulated repeated dosing scenarios for organic chemicals with a range of partitioning properties and compared the in vitro distributions over time. In single dose scenarios, for which only medium concentrations were available, simulated concentrations predicted measured concentrations with coefficients of determination (R 2) of 0.85–0.89, mean absolute error within a factor of two and model bias of nearly one. Repeat dose scenario simulations displayed model bias <2 within the cell lysate, and ∼1.5-3 in the medium. The concordance between simulated and available experimental data supports the predictive capacity of the IV-MBM DP v1.0 tool, but further evaluation as empirical data becomes available is warranted, especially for cellular concentrations.

Dynamic Modeling of Industrial Loop Reactors for Catalytic Ethylene (Co)polymerization: Pressure Safety Valves

AbstractIn industrial loop reactors, for catalytic ethylene (co)polymerization, the heat produced by polymerization can result in temperature and pressure increase, which in turn can lead to reactor breakage, explosion, and consequent release of toxic/flammable fluids in the environment. To predict the reactor temperature and pressure during ethylene (co)polymerization and assess the performance of presure safety valves (PSVs) in response to emergency accidents, an integrated mathematical approach is followed including catalyst kinetics, thermodynamics, and transport properties modeling. A catalytic ethylene (co)polymerization kinetic model is used to predict the catalyst activity variation with respect to reactor temperature and the heat produced by the polymerization reaction during a reaction runaway. The Sanchez–Lacombe equation of state (SL EOS) is utilized in order to predict the reactor pressure for different slurry mixture compositions and the slurry densities at different temperatures, pressures and solids weight fractions. Dynamic macroscopic mass and energy balances are derived to calculate the dynamic evolution of concentrations of the various molecular species as well as the temperature changes in the loop reactor. The model can predict the temperature and pressure increase rates and the maximum flow rate at the PSVs during the runaway.

A dynamic nutrient mass balance model for optimizing waste treatment in RAS and associated IMTA system

The combination of a Recirculation Aquaculture System (RAS) and Integrated Multi-trophic Aquaculture (IMTA) aims to optimize the utilization of nutrient input by recycling aquaculture wastes through use as food resources for co-cultured species. The coupling of RAS and IMTA also allows the development of new aquaculture products, potentially increasing economic return. A dynamic nutrient mass balance model was developed for a seawater-based RAS system with a hypothetical IMTA component. The model incorporated a three-dimensional trophic food web (Atlantic salmon, Ulva lactuca and an invertebrate grazing species) alongside traditional mechanical and biological (nitrification) filtration processes. The model simulated different waste treatment methods using biological and mechanical filtration only and further incorporating macroalgae filtration. Simulations showed that RAS in combination with macroalgae IMTA could reduce dissolved inorganic nitrogen (DIN) by 66% and dissolved inorganic phosphorus (DIP) by 31% compared with just RAS biological filtration. Using an optimal harvesting strategy, DIN and DIP waste removal rose to 94% and 45% respectively, and an increase in by-products biomass of 41%. The dynamic nutrient mass balance model provides a quantitative tool to better understand the fate of nutrients, and to optimize the design of the system. Although the commercial-scale development of this type of aquaculture system will depend on feasibility and profitability, the concept of combining RAS and IMTA provides important potential for sustainable aquaculture in the future.

Dynamic energy and mass balance model for an industrial alkaline water electrolyzer plant process

This paper proposes a parameter adjustable dynamic mass and energy balance simulation model for an industrial alkaline water electrolyzer plant that enables cost and energy efficiency optimization by means of system dimensioning and control. Thus, the simulation model is based on mathematical models and white box coding, and it uses a practicable number of fixed parameters. Zero-dimensional energy and mass balances of each unit operation of a 3 MW, and 16 bar plant process were solved in MATLAB functions connected via a Simulink environment. Verification of the model was accomplished using an analogous industrial plant of the same power and pressure range having the same operational systems design. The electrochemical, mass flow and thermal behavior of the simulation and the industrial plant were compared to ascertain the accuracy of the model and to enable modification and detailed representation of real case scenarios so that the model is suitable for use in future plant optimization studies. The thermal model dynamically predicted the real case with 98.7 % accuracy. Shunt currents were the main contributor to relative low Faraday efficiency of 86 % at nominal load and steady-state operation and heat loss to ambient from stack was only 2.6 % of the total power loss.