System Model Research Articles

Displacement Mechanism and Flow Characteristics of Polymer Particle Dispersion System Based on Capillary Bundle Model

During the development of oil reservoirs, a rapid increase in water cut following reservoir flooding leads to inefficient or ineffective circulation of injected water, rendering a significant portion of the remaining oil in the reservoir inaccessible. The displacement method using polymer particle dispersion systems effectively solves the issue of rapid water breakthrough in oil reservoirs. Owing to the particle phase separation phenomenon, polymer particles can selectively penetrate into the larger pores where water circulation is inefficient, enhance their flow resistance, and thereby achieve equilibrium displacement along with an increased swept volume. This paper investigates the heterogeneous distribution of polymer particles within a porous medium, incorporates the red blood cell dendrite concentration distribution theory from biological fluid mechanics, and develops a mathematical model to delineate the viscosity characteristics of polymer particle dispersion systems, taking into account the phase separation phenomenon. Building on this foundation, it formulates a capillary bundle model for the polymer particle dispersion system specifically designed for oil displacement and proceeds to determine its relative permeability curve. Simulation outcomes reveal that at a water saturation level of 0.063, the concentration of polymer particles in fractured large pore capillaries is markedly elevated, yet capillaries with a pore size under 26 μm remain devoid of polymer particles. With the increase of water saturation, the concentration of polymer particles in large pore capillaries reduces, whereas it progressively augments in medium pore capillaries. Upon reaching a peak water saturation of 0.751, capillaries smaller than 18 μm are entirely free of polymer particles. These findings suggest that the heterogeneous distribution of polymer particles markedly inhibits the percolation capabilities of the dispersed system following a water phase breakthrough, facilitating the entry of more dispersion into oil-laden capillaries and thus enhancing the flow capacity of the oil phase.

Coupling material and energy flow analysis with life cycle assessment to support circular strategies at the urban level

Abstract Purpose This study aims to investigate how the coupling of Material and Energy Flow Analysis (MEFA) with Life Cycle Assessment (LCA) under an urban metabolism (UM) perspective (referred to as the UM-LCA approach) can support the design, evaluation, and monitoring of urban-level circular strategies. For this purpose, we apply the UM-LCA approach to the urban area of Umeå (Sweden) by expanding the goal and scope of a recent MEFA study conducted by the authors of the article. Methods The modeling combines MEFA with LCA and is performed both retrospectively and prospectively. The MEFA was performed in the prior study following a bottom-up approach to map and quantify material and energy flows in the urban system at the sectoral level. The quantified flows are used in the present study to construct the life cycle inventory (LCI) model of the urban system. The LCI model is first used as a basis of the retrospective LCA (rLCA), which is conducted to assess the environmental performance of the urban system with its sectors. The LCI model is then modified according to future scenarios and is used as a basis of the prospective LCA (pLCA), which is performed to assess the environmental implications of implementing circular strategies in the future. Results and discussion The rLCA shows that the construction and household sectors are major drivers of environmental impacts in the urban system, with households being the largest contributors to 11 out of 12 analyzed impact categories. It also reveals the most impacting flows within these sectors, including food in households and steel in the construction sector. These findings indicate that the construction and household sectors and their most impacting flows should be prioritized in a circular strategy. Furthermore, the pLCA highlights that a future circular strategy promoting reductions in the material used in these two sectors could lead to higher reductions in all impact categories, ranging from 4.3 to 8.6%, than a strategy focused only on recycling, which could lead to reductions ranging from 0.2 to 1.2%. Conclusions This study concludes that the UM-LCA approach has great potential to comprehensively analyze, both retrospectively and prospectively, the environmental performance of an urban system providing valuable insights that could support policy makers in designing, assessing, and monitoring urban-level circular strategies. However, further research should address identified limitations of the UM-LCA approach (e.g., limited available data, inability to consider social and economic aspects) to facilitate its applicability and enhance its comprehensiveness.

Research on design strategy of public space service of commercial complex based on internet of things

The purpose of this study is to explore the design strategy of public space service of commercial complex based on the Internet of Things. By constructing a three-tier model of environmental energy consumption monitoring and management system for commercial complex, the application of network sensor technology is analyzed, and a data access interface based on Windows Communication Foundation (WCF) service is designed to realize batch hosting of WCF services and reduce the complexity of large-scale publishing services. In addition, this paper proposes a clustering method based on probabilistic topics (PTCM), which divides the service search space into probabilistic topics and effectively narrows the service search scope. The simulation results show that the algorithm shortens the shortest distance between mobile nodes and the average network distance, and improves the perceived service quality of the Internet of Things. This study not only provides new ideas and methods for the design of public space services in commercial complexes, but also provides useful reference for the application and promotion of Internet of Things technology in the field of public services.

Distributed HAPS-assisted communications in FSO/RF space-air-ground integrated networks

Space-air-ground integrated (SAGI) communication networks have been envisioned as one of the pillars of the next generation communications (6 G). This type of networks are expected to offer fairness and high quality of services in various scenarios where traditional terrestrial communication systems cannot efficiently support due to inherent limitations, e.g., limited coverage areas. In this paper, a distributed transmission scheme is proposed in a SAGI communication network that utilizes free-space-optical (FSO)/radio frequency (RF) links. More specifically, a set of N high altitude platform systems are cooperatively transmit the received signal to the ground station, using the decode-and-forward relaying protocol. For this system, generic analytical expressions for the outage probability (OP) have been derived that take into consideration the impact of turbulence, pointing errors, and atmospheric attenuation (for the FSO links) as well as the impact of composite fading (for the RF links). Moreover, asymptotic closed-form expressions for the OP are also presented, which are used to extract useful insights for the system under consideration. The numerical evaluated results that are illustrated reveal the impact of various system and channel models parameters on the system’s performance. From these results, it is shown that the proposed scheme outperforms a pure FSO-based relaying scheme, which has been used as a benchmark, under different environmental conditions.

Net primary production annual maxima in the North Atlantic projected to shift in the 21st century

Abstract. Shifts in the day of peak net primary production (NPP) were detected in different biogeochemical provinces of the North Atlantic (25–65° N). Most provinces displayed a shift toward earlier peak NPP, with the largest change points in the 21st century and in the northern parts of the domain. Furthermore, the occurrences of the first day with a mixed-layer depth (MLD) shallower than 40 m and the day of peak NPP are positively correlated over most of the domain. As was the case for the day of peak NPP, the largest change points for the day of MLD shallower than 40 m occur around or after the year 2000. Daily output from two fully coupled CMIP6 Earth system models, EC-Earth3-CC and NorESM2-LM, for the period 1750–2100 and under the SSP5-8.5 scenario, were used for the analysis. The ESM NPP data were compared with estimates derived from Carbon, Absorption and Fluorescence Euphotic-resolving (CAFE) satellite-based data. The ESMs showed significant differences from the CAFE model, though the timing of peak NPP was well captured for most provinces. The largest change points in the day of peak NPP occur earlier in EC-Earth3-CC than in NorESM2-LM. Although SSP5-8.5 is a scenario with very high warming, EC-Earth3-CC generates change points for most provinces in the early part of the 21st century, before the warming has deviated far from lower-emissions scenarios. NorESM2-LM displays the largest change points centered around the mid 21st century, with two out of eight provinces displaying the largest change point before the year 2050. The early timing of the detected shifts in some provinces in both ESMs suggests that similar shifts could already have been initiated or could start in the near future. This highlights the need for long-term monitoring campaigns in the North Atlantic.

Voltage stability assessment of the power system using novel line voltage collapse index

Nowadays, for the maximum utilization of the power available, power systems are operated at their maximum stability limit due to the scarcity of natural resources. In this situation, quick monitoring and control of the power systems are very necessary for the electrical operators. This paper presents a novel line voltage stability index based on V-Q sensitivity. The index is created utilizing the network’s ABCD parameters and is based on an exact transmission system model. The new index is evaluated in terms of ABCD parameters from the reactive power equation of the power system. The proposed line index can predict the voltage collapse under heavy MVA loading, heavy reactive loading, randomly chosen heavy reactive loading, and different N-1 contingencies conditions. This has also the capability to predict voltage stability under different contingencies. The proposed method is compared with four existing methods named line stability index (Lmn), fast voltage stability index (FVSI), line stability factor (Lqp), and line voltage stability index (LVSI). Results show that the critical situation of the power system that has been investigated by the proposed approach is more accurate than these four existing methods under different operating scenarios. The accuracy and applicability of the proposed method are investigated on IEEE 14-bus and IEEE 118-bus systems.

The carbonate pump feedback on alkalinity and the carbon cycle in the 21st century and beyond

Abstract. Ocean acidification is likely to impact all stages of the ocean carbonate pump, i.e. the production, export, dissolution and burial of biogenic CaCO3. However, the associated feedback on anthropogenic carbon uptake and ocean acidification has received little attention. It has previously been shown that Earth system model (ESM) carbonate pump parameterizations can affect and drive biases in the representation of ocean alkalinity, which is critical to the uptake of atmospheric carbon and provides buffering capacity towards associated acidification. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), we show divergent responses of CaCO3 export at 100 m this century, with anomalies by 2100 ranging from −74 % to +23 % under a high-emission scenario. The greatest export declines are projected by ESMs that consider pelagic CaCO3 production to depend on the local calcite/aragonite saturation state. Despite the potential effects of other processes on alkalinity, there is a robust negative correlation between anomalies in CaCO3 export and salinity-normalized surface alkalinity across the CMIP6 ensemble. Motivated by this relationship and the uncertainty in CaCO3 export projections across ESMs, we perform idealized simulations with an ocean biogeochemical model and confirm a limited impact of carbonate pump anomalies on 21st century ocean carbon uptake and acidification. However, we highlight a potentially abrupt shift, between 2100 and 2300, in the dissolution of CaCO3 from deep to subsurface waters when the global-scale mean calcite saturation state reaches about 1.23 at 500 m (likely when atmospheric CO2 reaches 900–1100 ppm). During this shift, upper ocean acidification due to anthropogenic carbon uptake induces deep ocean acidification driven by a substantial reduction in CaCO3 deep dissolution following its decreased export at depth. Although the effect of a diminished carbonate pump on global ocean carbon uptake and surface ocean acidification remains limited until 2300, it can have a large impact on regional air–sea carbon fluxes, particularly in the Southern Ocean.

Viable System Model (VSM): A New Approach to Accounting Information System Development Model

This article discusses the potential for using the Viable System Model (VSM) as a new approach in developing accounting information systems. This article takes the form of a systematic literature review. The analysis was carried out using a comparative approach between the System Development Life Cycle (SDLC-Model) and the Viable System Model (VSM) in general and specifically in the field of accounting and accounting information systems. The SDLC is primarily focused on the development and management of software or systems, while the VSM is concerned with the broader understanding and management of complex organizations. Both concepts have their unique applications and are important in their respective domains. The results of the study show that the VSM has a more holistic approach in developing accounting information systems. The research results also show that VSM is more suitable for developing accounting information systems in organizations that are complex, flexible, and adaptive to the speed of change in the company’s ongoing organizational business environment. The VSM provides a framework for understanding how organizations and systems can adapt to changing environments and maintain viability. It is particularly useful for complex organizations that need to respond to dynamic conditions. Keywords: accounting information system development, viable system model, system development life cycle

Efficient spin-up of Earth System Models using sequence acceleration.

Marine and terrestrial biogeochemical models are key components of the Earth System Models (ESMs) used to project future environmental changes. However, their slow adjustment time also hinders effective use of ESMs because of the enormous computational resources required to integrate them to a pre-industrial equilibrium. Here, a solution to this "spin-up" problem based on "sequence acceleration", is shown to accelerate equilibration of state-of-the-art marine biogeochemical models by over an order of magnitude. The technique can be applied in a "black box" fashion to existing models. Even under the challenging spin-up protocols used for Intergovernmental Panel on Climate Change (IPCC) simulations, this algorithm is 5 times faster. Preliminary results suggest that terrestrial models can be similarly accelerated, enabling a quantification of major parametric uncertainties in ESMs, improved estimates of metrics such as climate sensitivity, and higher model resolution than currently feasible.

Exploring the prospects, advancements, and challenges of in vitro modeling of the heart-brain axis

Research on bidirectional communication between the heart and brain has often relied on studies involving nonhuman animals. Dependance on animal models offer limited applicability to humans and a lack of high-throughput screening. Recently, the field of 3D cell biology, specifically organoid technology, has rapidly emerged as a valuable tool for studying interactions across organ systems, i.e., gut-brain axis. The initial success of organoid models indicates the usefulness of 3D cultures for elucidating the intricate interactivity of the autonomic nervous system and overall health. This perspective aims to explore the potential of advancing in vitro modeling of the heart-brain axis by discussing the benefits, applications, and adaptability of organoid technologies. We closely examine the current state of brain organoids in conjunction with the advancements of cardiac organoids. Moreover, we explore the use of combined organoid systems to investigate pathophysiology and provide a platform for treatment discovery. Finally, we address the challenges that accompany the use of 3D models for studying the heart-brain axis with an emphasis on generating tailored engineering strategies for further refinement of dynamic organ system modeling in vitro.

Sustainable energy storage solutions for coal-fired power plants: A comparative study on the integration of liquid air energy storage and hydrogen energy storage systems

With the majority of the world's energy demand still reliant on fossil fuels, particularly coal, mitigating the substantial carbon dioxide (CO2) emissions from coal-fired power plants is imperative for achieving a net-zero carbon future. Energy storage technologies offer a viable solution to provide better flexibility against load fluctuations and reduce the carbon footprint of coal-fired power plants by minimizing exergy losses, thereby achieving better energy efficiency. This work focuses on developing two such energy storage technologies: Liquid Air Energy Storage (LAES) and Hydrogen Energy Storage (HES), and their integration strategies with a sub-critical coal-fired power plant. The performance of the integrated systems is analyzed based on key parameters like energy storage capacity, net unit power output during charging and discharging, round-trip efficiencies, and net unit efficiencies at different operating load conditions of the plant. Our results show that during the charging cycles, by increasing the air flow rate in LAES and the hydrogen production rate in HES, the net unit efficiency of the integrated plant decreases by 3–10% at different load conditions, while the energy-based round-trip efficiency increases with increasing liquid air and hydrogen flow rates during the discharge cycles. For the HES system, utilization of the produced hydrogen in the fuel cells gives 40–50% better roundtrip efficiencies than co-firing hydrogen in the boiler at full and minimum load and it increases with increasing hydrogen flow rates. While HES has shown a better overall net unit efficiency (41.5%, in fuel cell scenario) of the integrated unit than the LAES system (40%) for the base case operation, LAES shows superior round-trip efficiencies when operated at higher liquid air discharge flow rates (>80 kg/s). The results provide insights into the system modeling of LAES and HES integrated with a sub-critical coal power plant, contributing to the advancement of sustainable energy storage solutions.

Application of Fuzzy Control and Neural Network Control in the Commercial Development of Sustainable Energy System

Sustainable energy systems (SESs) occupy a prominent position in the modern global energy landscape. The purpose of this study is to explore the application of fuzzy control and neural network control in photovoltaic systems to improve the power generation efficiency and stability of the system. By establishing the mathematical model of a photovoltaic system, the nonlinear and uncertain characteristics of photovoltaic system are considered. Fuzzy control and neural network control are used to control the system, and their performance is verified by experiments. The experimental results show that under the conditions of low light and moderate temperature, the fuzzy neural network control achieves a 3.33% improvement in power generation efficiency compared with the single control strategy. Meanwhile, the system can still maintain relatively stable operation under different environmental conditions under this comprehensive control. This shows that fuzzy neural network control has significant advantages in improving power generation efficiency and provides beneficial technical support and guidance for the commercial development of SESs.

Research on dynamic stability of rolling missiles employing direct/aerodynamic force compound control

The direct/aerodynamic force compound control can enhance the maneuverability and response characteristics of missiles, and the dynamic stabilization is the precondition of normal operation for rolling missiles. Aiming at the stability problem caused by the cross-coupling effect of rolling missiles employing direct/aerodynamic force compound control, proposing a typical topological control system structure described by the complex coefficient theory, and deducing the dynamic stability conditions. Firstly, the mathematic model is established based on the kinematics and dynamics theories of rotating airframes and the direct/aerodynamic force compound control mechanism. Then, a three-loop autopilot and the direct/aerodynamic force ratio distribution method are designed to establish the complex summation model of the compound control system by selecting suitable complex variables. Furthermore, deducing the dynamic stability conditions and verifying them by numerical simulations. Finally, the stable regions of the rolling missile in different cases are obtained and found to be influenced by many factors, such as parameters of the autopilot, hybrid force distribution proportion and rolling rate. The derived dynamic stability criterion is effective for evaluating the stability of rolling missiles employing direct/aerodynamic force compound control and the research method used in this paper can provide reference for the stability study of strongly coupled nonlinear systems.

Experimental validation of the appropriate channel model for an indoor Visible Light Communication system

Visible light communication (VLC) is a technology with significant potential to revolutionize indoor communication performance and satisfy the demands of fifth-generation (5G) and beyond technologies. To achieve an efficient VLC system that delivers optimal performance and coverage, it is imperative to create a reliable channel model. As a result, this research is centered around the evaluation of existing channel models for planning the VLC network coverage within indoor environments. The primary focus of this study is to enforce three types of channel models, Line of Sight (LoS), Nakagawa’s first reflection model, and the Spherical model through MATLAB simulations and obtain simulation results by varying the distance parameter. Furthermore, this research intends to implement a physical prototype representing a real-world scenario, and thereby determine the nearest channel model that aligns with the physical measurements obtained from the physical prototype.

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Purpose To provide high torques needed to move a robot’s links, electric actuators are followed by a transmission system with a high transmission rate. For instance, gear ratios of 100:1 are often used in the joints of a robotic manipulator. This results into an actuator with large mechanical impedance (also known as nonback-drivable actuator). This in turn generates high contact forces when collision of the robotic mechanism occur and can cause humans’ injury. Another disadvantage of electric actuators is that they can exhibit overheating when constant torques have to be provided. Comparing to electric actuators, pneumatic actuators have promising properties for robotic applications, due to their low weight, simple mechanical design, low cost and good power-to-weight ratio. Electropneumatically actuated robots usually have better friction properties. Moreover, because of low mechanical impedance, pneumatic robots can provide moderate interaction forces which is important for robotic surgery and rehabilitation tasks. Pneumatic actuators are also well suited for exoskeleton robots. Actuation in exoskeletons should have a fast and accurate response. While electric motors come against high mechanical impedance and the risk of causing injuries, pneumatic actuators exhibit forces and torques which stay within moderate variation ranges. Besides, unlike direct current electric motors, pneumatic actuators have an improved weight-to-power ratio and avoid overheating problems. Design/methodology/approach The aim of this paper is to analyze a nonlinear optimal control method for electropneumatically actuated robots. A two-link robotic exoskeleton with electropneumatic actuators is considered as a case study. The associated nonlinear and multivariable state-space model is formulated and its differential flatness properties are proven. The dynamic model of the electropneumatic robot is linearized at each sampling instance with the use of first-order Taylor series expansion and through the computation of the associated Jacobian matrices. Within each sampling period, the time-varying linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. An H-infinity controller is designed for the linearized model of the robot aiming at solving the related optimal control problem under model uncertainties and external perturbations. An algebraic Riccati equation is solved at each time-step of the control method to obtain the stabilizing feedback gains of the H-infinity controller. Through Lyapunov stability analysis, it is proven that the robot’s control scheme satisfies the H-infinity tracking performance conditions which indicate the robustness properties of the control method. Moreover, global asymptotic stability is proven for the control loop. The method achieves fast convergence of the robot’s state variables to the associated reference trajectories, and despite strong nonlinearities in the robot’s dynamics, it keeps moderate the variations of the control inputs. Findings In this paper, a novel solution has been proposed for the nonlinear optimal control problem of robotic exoskeletons with electropneumatic actuators. As a case study, the dynamic model of a two-link lower-limb robotic exoskeleton with electropneumatic actuators has been considered. The dynamic model of this robotic system undergoes first approximate linearization at each iteration of the control algorithm around a temporary operating point. Within each sampling period, this linearization point is defined by the present value of the robot’s state vector and by the last sampled value of the control inputs vector. The linearization process relies on first-order Taylor series expansion and on the computation of the associated Jacobian matrices. The modeling error which is due to the truncation of higher-order terms from the Taylor series is considered to be a perturbation which is asymptotically compensated by the robustness of the control algorithm. To stabilize the dynamics of the electropneumatically actuated robot and to achieve precise tracking of reference setpoints, an H-infinity (optimal) feedback controller is designed. Actually, the proposed H-infinity controller for the model of the two-link electropneumatically actuated exoskeleton achieves the solution of the associated optimal control problem under model uncertainty and external disturbances. This controller implements a min-max differential game taking place between: (i) the control inputs which try to minimize a cost function which comprises a quadratic term of the state vector’s tracking error and (ii) the model uncertainty and perturbation inputs which try to maximize this cost function. To select the stabilizing feedback gains of this H-infinity controller, an algebraic Riccati equation is being repetitively solved at each time-step of the control method. The global stability properties of the H-infinity control scheme are proven through Lyapunov analysis. Research limitations/implications Pneumatic actuators are characterized by high nonlinearities which are due to air compressibility, thermodynamics and valves behavior and thus pneumatic robots require elaborated nonlinear control schemes to ensure their fast and precise positioning. Among the control methods which have been applied to pneumatic robots, one can distinguish differential geometric approaches (Lie algebra-based control, differential flatness theory-based control, nonlinear model predictive control [NMPC], sliding-mode control, backstepping control and multiple models-based fuzzy control). Treating nonlinearities and fault tolerance issues in the control problem of robotic manipulators with electropneumatic actuators has been a nontrivial task. Practical implications The novelty of the proposed control method is outlined as follows: preceding results on the use of H-infinity control to nonlinear dynamical systems were limited to the case of affine-in-the-input systems with drift-only dynamics. These results considered that the control inputs gain matrix is not dependent on the values of the system’s state vector. Moreover, in these approaches the linearization was performed around points of the desirable trajectory, whereas in the present paper’s control method the linearization points are related with the value of the state vector at each sampling instance as well as with the last sampled value of the control inputs vector. The Riccati equation which has been proposed for computing the feedback gains of the controller is novel, so is the presented global stability proof through Lyapunov analysis. This paper’s scientific contribution is summarized as follows: (i) the presented nonlinear optimal control method has improved or equally satisfactory performance when compared against other nonlinear control schemes that one can consider for the dynamic model of robots with electropneumatic actuators (such as Lie algebra-based control, differential flatness theory-based control, nonlinear model-based predictive control, sliding-mode control and backstepping control), (ii) it achieves fast and accurate tracking of all reference setpoints, (iii) despite strong nonlinearities in the dynamic model of the robot, it keeps moderate the variations of the control inputs and (iv) unlike the aforementioned alternative control approaches, this paper’s method is the only one that achieves solution of the optimal control problem for electropneumatic robots. Social implications The use of electropneumatic actuation in robots exhibits certain advantages. These can be the improved weight-to-power ratio, the lower mechanical impedance and the avoidance of overheating. At the same time, precise positioning and accurate execution of tasks by electropneumatic robots requires the application of elaborated nonlinear control methods. In this paper, a new nonlinear optimal control method has been developed for electropneumatically actuated robots and has been specifically applied to the dynamic model of a two-link robotic exoskeleton. The benefit from using this paper’s results in industrial and biomedical applications is apparent. Originality/value A comparison of the proposed nonlinear optimal (H-infinity) control method against other linear and nonlinear control schemes for electropneumatically actuated robots shows the following: (1) Unlike global linearization-based control approaches, such as Lie algebra-based control and differential flatness theory-based control, the optimal control approach does not rely on complicated transformations (diffeomorphisms) of the system’s state variables. Besides, the computed control inputs are applied directly on the initial nonlinear model of the electropneumatic robot and not on its linearized equivalent. The inverse transformations which are met in global linearization-based control are avoided and consequently one does not come against the related singularity problems. (2) Unlike model predictive control (MPC) and NMPC, the proposed control method is of proven global stability. It is known that MPC is a linear control approach that if applied to the nonlinear dynamics of the electropneumatic robot, the stability of the control loop will be lost. Besides, in NMPC the convergence of its iterative search for an optimum depends on initialization and parameter values selection and consequently the global stability of this control method cannot be always assured. (3) Unlike sliding-mode control and backstepping control, the proposed optimal control method does not require the state-space description of the system to be found in a specific form. About sliding-mode control, it is known that when the controlled system is not found in the input-output linearized form the definition of the sliding surface can be an intuitive procedure. About backstepping control, it is known that it cannot be directly applied to a dynamical system if the related state-space model is not found in the triangular (backstepping integral) form. (4) Unlike PID control, the proposed nonlinear optimal control method is of proven global stability, the selection of the controller’s parameters does not rely on a heuristic tuning procedure, and the stability of the control loop is assured in the case of changes of operating points. (5) Unlike multiple local models-based control, the nonlinear optimal control method uses only one linearization point and needs the solution of only one Riccati equation so as to compute the stabilizing feedback gains of the controller. Consequently, in terms of computation load the proposed control method for the electropneumatic actuator’s dynamics is much more efficient.

Parametric modeling and performance assessment of a novel cogeneration system of biomass chemical looping gasification driven by solar energy

Parametric modeling and performance assessment of a novel cogeneration system of biomass chemical looping gasification driven by solar energy

Assessing acetone for the GISS ModelE2.1 Earth system model

Abstract. Acetone is an abundant volatile organic compound (VOC) in the atmosphere, with important influences on ozone and oxidation capacity. Direct sources include chemical production from other VOCs and anthropogenic emissions, terrestrial vegetation, biomass-burning emissions, and ocean production. Sinks include chemical loss, deposition onto the land surface, and ocean uptake. Acetone also has a lifetime that is long enough to allow transport and reactions with other compounds remote from its sources. The NASA Goddard Institute for Space Studies (GISS) Earth system model ModelE2.1 simulates a variety of Earth system interactions. Previously, acetone had a very simplistic representation in the ModelE chemical scheme. This study assesses a more sophisticated acetone scheme in which acetone is a full 3-dimensional tracer with explicit sources, sinks, and atmospheric transport. We first evaluate the new global acetone budget in the context of past literature. Estimated source and sink fluxes fall within the range of previous models, although total atmospheric burden and lifetime are at the lower end of the published literature. Acetone's new representation in ModelE2.1 also results in more realistic spatial and vertical distributions, which we compare against previous models and field observations. The seasonality of acetone-related processes was also studied in conjunction with field measurements, and these comparisons show promising agreement but also shortcomings at high-emission urban locations, where the model's resolution is too coarse to capture the true behavior. Finally, we conduct a variety of sensitivity studies that explore the influence of key parameters on the acetone budget and its global distribution. An impactful finding is that the production of acetone from precursor hydrocarbon oxidation has strong leverage on the overall chemical source, indicating the importance of accurate molar yields. Overall, our implementation is one that corroborates with previous studies and marks a significant improvement in the development of the acetone tracer in GISS ModelE2.1.

Improving seasonal predictions of German Bight storm activity

Abstract. Extratropical storms are one of the major coastal hazards along the coastline of the German Bight, the southeastern part of the North Sea, and a major driver of coastal protection efforts. However, the predictability of these regional extreme events on a seasonal scale is still limited. We therefore improve the seasonal prediction skill of the Max Planck Institute Earth System Model (MPI-ESM) large-ensemble decadal hindcast system for German Bight storm activity (GBSA) in winter. We define GBSA as the 95th percentiles of three-hourly geostrophic wind speeds in winter, which we derive from mean sea-level pressure (MSLP) data. The hindcast system consists of an ensemble of 64 members, which are initialized annually in November and cover the winters of 1960/61–2017/18. We consider both deterministic and probabilistic predictions of GBSA, for both of which the full ensemble produces poor predictions in the first winter. To improve the skill, we observe the state of two physical predictors of GBSA, namely 70 hPa temperature anomalies in September, as well as 500 hPa geopotential height anomalies in November, in areas where these two predictors are correlated with winter GBSA. We translate the state of these predictors into a first guess of GBSA and remove ensemble members with a GBSA prediction too far away from this first guess. The resulting subselected ensemble exhibits a significantly improved skill in both deterministic and probabilistic predictions of winter GBSA. We also show how this skill increase is associated with better predictability of large-scale atmospheric patterns.

First comprehensive assessment of industrial-era land heat uptake from multiple sources

Abstract. The anthropogenically intensified greenhouse effect has caused a radiative imbalance at the top of the atmosphere during the industrial period. This, in turn, has led to an energy surplus in various components of the Earth system, with the ocean storing the largest part. The land contribution ranks second with the latest observational estimates based on borehole temperature profiles, which quantify the terrestrial energy surplus to be 6 % in the last 5 decades, whereas studies based on state-of-the-art climate models scale it down to 2 %. This underestimation stems from land surface models (LSMs) having a subsurface that is too shallow, which severely constrains the land heat uptake simulated by Earth system models (ESMs). A forced simulation of the last 2000 years with the Max Planck Institute ESM (MPI-ESM) using a deep LSM captures 4 times more heat than the standard shallow MPI-ESM simulations in the historical period, well above the estimates provided by other ESMs. However, deepening the LSM does not remarkably affect the simulated surface temperature. It is shown that the heat stored during the historical period by an ESM using a deep LSM component can be accurately estimated by considering the surface temperatures simulated by the ESM using a shallow LSM and propagating them with a standalone forward model. This result is used to derive estimates of land heat uptake using all available observational datasets, reanalysis products, and state-of-the-art ESM experiments. This approach yields values of 10.5–16.0 ZJ for 1971–2018, which are 12 %–42 % smaller than the latest borehole-based estimates (18.2 ZJ).

Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model

Abstract. Emissions of anthropogenic aerosol and their precursors are often prescribed in global aerosol models. Most of these emissions are spatially heterogeneous at model grid scales. When remapped from low-resolution data, the spatial heterogeneity in emissions can be lost, leading to large errors in the simulation. It can also cause the conservation problem if non-conservative remapping is used. The default anthropogenic emission treatment in the Energy Exascale Earth System Model (E3SM) is subject to both problems. In this study, we introduce a revised emission treatment for the E3SM Atmosphere Model (EAM) that ensures conservation of mass fluxes and preserves the original emission heterogeneity at the model-resolved grid scale. We assess the error estimates associated with the default emission treatment and the impact of improved heterogeneity and mass conservation in both globally uniform standard-resolution (∼ 165 km) and regionally refined high-resolution (∼ 42 km) simulations. The default treatment incurs significant errors near the surface, particularly over sharp emission gradient zones. Much larger errors are observed in high-resolution simulations. It substantially underestimates the aerosol burden, surface concentration, and aerosol sources over highly polluted regions, while it overestimates these quantities over less-polluted adjacent areas. Large errors can persist at higher elevation for daily mean estimates, which can affect aerosol extinction profiles and aerosol optical depth (AOD). We find that the revised treatment significantly improves the accuracy of the aerosol emissions from surface and elevated sources near sharp spatial gradient regions, with significant improvement in the spatial heterogeneity and variability of simulated surface concentration in high-resolution simulations. In the next-generation E3SM running at convection-permitting scales where the resolved spatial heterogeneity is significantly increased, the revised emission treatment is expected to better represent the aerosol emissions as well as their lifecycle and impacts on climate.