Combined System Research Articles

Removal of melanoidin from baker yeast plant wastewater: A comparative study on chemical and biological processes

Dark brown color and large quantities of chemical oxygen demand (COD) are challenging for the successful treatment of molasses-based baker's yeast (BY) wastewater. In this study, the sequential biological and chemical coagulation processes were compared in terms of their ability to remove color and COD from industrial molasses-based BY wastewater. In the sequential chemical-biological processes, using the desired dosages of ferric chloride (FeCl3, 4 g/L) and calcium oxide (CaO, 2 % (w/v)) as coagulating agents, the color and COD removal were 90.6 % and 57 %, respectively. The COD removal of the samples from chemical pre-treated wastewater in an aerated biological reactor (reactor A) was improved to 78 %. In sequential biological-chemical processes with extended aeration (bioreactor A), the COD and color removal were 89.1 % and 93.7 %, respectively. The chemical post-treating of the effluent of the combined anaerobic-aerobic system (reactor C) led to COD and color removal of 80.8 % and 94.65 %, respectively. According to experimental findings, the chemical post-treatment was more efficient than the chemical pre-treatment process. This study offers new insights into the utilization of combined systems for the efficient removal of color and COD from industrial wastewater.

Joint mode selection and resource allocation for cellular V2X communication using distributed deep reinforcement learning under 5G and beyond networks

Vehicle-to-everything (V2X) communication via cellular networks is a promising technique for 5G and beyond networks. The cars interact directly with one another, as well as with the infrastructure and various vehicles on the road, in this mode. It enables the interchange of time-sensitive and safety-critical data. Despite these benefits, unstable vehicle-to-vehicle (V2V) communications, insufficient channel status information, high transmission overhead, and the considerable communication cost of centralized resource allocation systems all pose challenges for defense applications. To address these difficulties, this study proposes a combined mode selection and resource allocation system based on distributed deep reinforcement learning (DRL) to optimize the overall network sum rate while maintaining the reliability and latency requirements of V2V pairs and the data rate of V2R connections. Because the optimization issue is non-convex and NP-hard, it can’t be solved directly. To tackle this problem, the defined problem is first translated into machine learning form using the Markov decision process (MDP) to construct the reward function and decide whether agent would conduct the action. Following that, the distributed coordinated duelling deep Q-network (DDQN) method based on prioritized sampling is employed to improve mode selection and resource allocation. This approach learns the action-value distribution by estimating both the state-value and action advantage functions using duelling deep networks. The results of the simulation show that the suggested scheme outperforms state-of-the-art decentralized systems in terms of sum rate and QoS satisfaction probability.

Development and Application of a High-Precision Portable Digital Compass System for Improving Combined Navigation Performance

There are not many high-precision, portable digital compass solutions available right now that can enhance combined navigation systems’ overall functionality. Additionally, there is a dearth of writing about these products. This is why a tunnel magnetoresistance (TMR) sensor-based high-precision portable digital compass system is designed. First, the least-squares method is used to compensate for compass inaccuracy once the ellipsoid fitting method has corrected manufacturing and installation errors in the digital compass system. Second, the digital compass’s direction angle data is utilized to offset the combined navigation system’s mistake. The final objective is to create a high-performing portable TMR digital compass system that will enhance the accuracy and stability of the combined navigation system (abbreviated as CNS). According to the experimental results, the digital compass’s azimuth accuracy was 4.1824° before error compensation and 0.4580° after it was applied. The combined navigation system’s path is now more accurate overall and is closer to the reference route than it was before the digital compass was added. Furthermore, compared to the combined navigation route without the digital compass, the combined navigation route with the digital compass included is more stable while traveling through the tunnel. It is evident that the digital compass system’s design can raise the integrated navigation system’s accuracy and stability. The integrated navigation system’s overall performance may be somewhat enhanced by this approach.

Design Issue Analysis and Operation Effect Evaluation of Large-Scale Storage Tank

In order to address the issue of combined sewer overflows (CSOs), W city has constructed a large-scale storage tank with a volume of 220,000 m3. The storage tank is planned for CSO control in the near term and stormwater runoff pollution control in the long term. However, the actual operation of the storage tank is unsatisfactory. This paper elucidates the design scheme and operation mode of the tank and analyzes the challenges encountered during its design and operation. A storm water management model (SWMM) model was constructed to simulate the effect of the storage tank working in a combined sewer system (CSS), a separate sewer system (SSS) and a decentralized storage situation. This study determined that during the 2022 rainy season, the actual reduction in pollutants by the storage tank was only about 60% of the designed value. As a result, the inadequate treatment capacity of the downstream wastewater treatment plant (WWTP) resulted in the water being retained in the tank for a long time, leading to unsatisfactory operation outcomes. If the storage tank works in SSS and the problem of water retention can be solved, it could reduce the total runoff volume by 30% and the total amount of pollutants by 40% during the same rainy season. At the same time, under the premise of constant total storage volume, if decentralized storage tanks were used to control runoff pollution, the reduction effect can be increased by up to 11.6% compared with that of the centralized storage.

Laser-induced damages to charge coupled devices with combined nanosecond/picosecond short-pulse lasers

The research on laser induced breakdown mechanism of charge coupled devices (CCDs) brings new insights into photoelectric countermeasures. So far combined laser irradiation has been proved to be a more effective measure to destroy CCD. Due to the limitation of short-pulse laser combination method, the mechanism of CCD damage caused by combined short-pulse laser remains unexplored. Here, the distribution of temperature and stress field during the interaction between a combined short-pulse laser and a CCD is analyzed. A nanosecond/picosecond combined short-pulse laser system based on Stimulated Brillouin Scattering (SBS) pulse compression technique is designed. The damage threshold (DT) and properties of CCD by combined laser irradiation are characterized. The results show that the complete DT of combined laser induced CCD breakdown is only 103 mJ/cm2, which is only 44% of that of picosecond laser. The main cause of combined short-pulse laser induced CCD breakdown is short circuit (SC) between silicon substrate and silicon electrode.

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches

Abstract Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer flow prediction and RDII estimation based on field monitoring data. The study implemented feature engineering for extracting physically significant factors in sewer flow modelling and investigated the importance of the relevant factors. The results from two case studies indicated the superior capability of machine learning models in RDII estimation in the combined and separated sewer systems, and LSTM model outperformed the two models. Compared to traditional methods, machine learning models were capable of simulating the temporal variation in RDII processes and improved prediction accuracy for peak flows and RDII volumes in storm events.

Day-ahead optimization of integrated electricity and thermal system combining multiple types of demand response strategies and situation awareness technology

Under the dual pressure of energy shortage and environmental pollution, relying only on increasing the installed capacity of units and line transmission capacity cannot cope with the conflict between the growth of power demand and the difficulty of grid expansion in the long run. Demand response conducts users to change their energy consumption habits through system-issued electricity prices or incentives, so that the demand of the load side can be adjusted flexibly, which can further enhance the consumption of wind power and improve system economics. Based on the background of diversified energy use, this paper proposes a day-ahead optimal scheduling strategy for integrated electricity and thermal system considering multiple types of demand response. Firstly, the dispatch framework of integrated electricity and thermal system with the situation awareness technology is constructed to address uncertainties of Renewable Energy Sources, thus helping system mitigate uncertain risks. Secondly, the demand response mechanism of power system and regional thermal inertia of thermal system are modeled, respectively, to uncover the principles of load regulation of different energy systems; Then, a day-ahead optimal scheduling model for the integrated thermal and electricity system is developed, and the consumption evaluation index is integrated to indicate energy utilization efficiency; Finally, a combined electric-heat system model with 39-node grid and 6-node heat network is developed, and the positive effects of considering multiple types of demand response and situation awareness technology on promoting the consumption of renewable energy and improving the energy efficiency of the system are verified through the case study.

VIRTUAL MOUSE WITH INTEGRATED CHATBOT

Notably, the research addresses challenges in achieving precision and user adaptability within Virtual Gesture Systems. Employing a systematic methodology, the study utilizes cutting-edge hardware and software to capture and analyze data related to hand motion. Additionally, this research integrates a voice assistant-based chatbot with limited functions, expanding the scope of interaction possibilities. The results offer a comprehensive evaluation of the combined Virtual Gesture System and voice-assisted chatbot. This evaluation includes a comparative analysis of accuracy, efficiency, and user satisfaction against existing systems in the field. The ensuing discussion interprets the findings, addressing initial research questions and outlining implications for future development. The integration of a voice assistant-based chatbot enhances the versatility of the system, opening avenues for streamlined and user-friendly interactions. Despite inherent limitations, this research significantly contributes to the understanding of Virtual Gesture Systems, presenting a novel approach to human-computer interaction across diverse domains.

Mechanism underlying effects of CaO-MgO combined expansive agent on hydration kinetics of cement-based systems

With the order of better understanding the early hydration process and reaction mechanism of CaO-MgO combined expansion agent-involved cement-based systems (CMEA-CBS), CMEA dosage, CaO to MgO ratio (Ca/Mg), MgO activity, hydration temperature, and water-binder ratios (w/b) were chosen as the influencing factor. Accordingly, isothermal calorimetry was implemented to analyze the hydration heat release law, and the Krstulovic–Dabic model was applied to investigate the hydration kinetic. Moreover, the activation energy of CMEA-CBS was calculated. The findings of this study are as follows. The incorporation of CMEA can accelerate the hydration of cementitious systems. Hydration temperature increase markedly promote the hydration reaction of CMEA-CBS. The hydration reaction of CMEA-CBS is a complex associated reaction process dominated by multiple reaction mechanisms in sequence. At both 20 °C and 45 °C, the hydration process of CMEA-involved cement-based systems experienced three stages of crystallization nucleation and crystal growth (NG), phase boundary reaction (I), and diffusion (D), and the hydration mechanism was NG → I → D. However, the hydration of CMEA-CBS at 65 °C switched from the NG stage to the D stage directly. The hydration promotion effect of increasing temperature on I and D process of CMEA-CBS is less than I and D process of pure cement. Compared to the other groups, the temperature increase had the least effect on the early hydration process of 10%-C1M1-M-0.4 with the lowest apparent activation energy.

Enhancing the Quality of Low-Salt Silver Carp (Hypophthalmichthys molitrix) Surimi Gel Using Psyllium Husk Powder: An Orthogonal Experimental Approach

Low-salt surimi production is crucial as it addresses health concerns related to sodium intake while maintaining the quality and shelf-life of seafood products. This research focused on optimizing the gelation conditions for silver carp surimi with the addition of psyllium husk powder at low salt concentrations (0.5% and 1%, w/w) to investigate the effects of psyllium husk powder concentration, temperature, and time on gel strength and water-holding capacity. The quality was assessed in terms of gel strength and water-holding capacity. Following a single-factor exploration, a three-level orthogonal experiment was designed to evaluate the influence of these three variables using a combined scoring system. Results indicated that psyllium husk powder levels between 0.1% and 0.3% (w/w) enhanced gel strength and water-holding capacity. The optimal conditions were identified as follows: 1% (w/w) NaCl with 0.2% (w/w) psyllium husk powder for 2.5 h at 35 °C, and 0.5% (w/w) NaCl with 0.3% (w/w) psyllium husk powder for 3 h at 35 °C. Texture profile analysis revealed that psyllium husk powder increased the hardness of the surimi gel, promoting myosin cross-linking and denser gel structure. Compared to traditional surimi gel, which relies on ionic bonds, the optimized gel showed higher levels of disulfide cross-linking and enhanced hydrophobic interactions, resulting in a stronger gel structure. Sensory evaluation suggested that surimi gels with psyllium husk powder were perceived as better than those without psyllium husk powder. The study concludes that selecting the appropriate psyllium husk powder quantity and thermal processing conditions based on salt concentration can significantly improve the quality of low-salt surimi gels. Error analysis using one-way ANOVA was performed on all experimental data and (p < 0.05) indicated the significant difference.

Calibration and pose measurement of a combined vision sensor system for industrial robot grasping of brackets

Abstract Recently, visual sensing measurement and its application in industrial robot operations have been widely researched, promoting the development of instrumentation and automation. This study proposes a combined vision sensor system for robot grasping, focusing on combined sensor system calibration and bracket pose measurements. The system configuration and working strategy of the combined vision system are introduced. Thereafter, the calibration of the combined vision coordinate systems is presented, wherein a global vision system (GVS) acts as the external measuring equipment for accurately calibrating the local vision. Furthermore, a pose estimation method using a local vision system (LVS) is proposed, including morphology-based image enhancement and principal component analysis (PCA)-based corner recognition methods. Verification experiments, including combined calibration and bracket pose measurements, were performed to validate the effectiveness and accuracy of the proposed combined vision measurement strategy. The results demonstrated that the proposed system applies to industrial robot grasping of brackets. In addition, the proposed robot-sensor calibration method improves calibration accuracy. Finally, the proposed corner detection method is effective and accurate for different bracket detection applications. This study provides a system that improves robot grasping results by considering key factors, such as vision measurement accuracy, and calibration methods.

Combined Supercritical CO2 Brayton Cycle and Organic Rankine Cycle for Exhaust Heat Recovery

Abstract In order to reduce energy consumption and related CO2 emissions, waste heat recovery is considered a viable opportunity in several economic sectors, with a focus on industry and transportation. Among different proposed technologies, thermodynamic cycles using suitable organic working fluids seem to be promising options, and the possibility of combining two different cycles improves the final recovered energy. In this paper, a combination of Brayton and Rankine cycles is proposed: the upper cycle has supercritical carbon dioxide (sCO2) as its working fluid, while the bottomed Rankine section is realized by an organic fluid (organic Rankine cycle (ORC)). This combined unit is applied to recover the exhaust energy from the flue gases of an internal combustion engine (ICE) for the transportation sector. The sCO2 Brayton cycle is directly facing the exhaust gases, and it should dispose of a certain amount of energy at lower pressure, which can be further recovered by the ORC unit. A specific mathematical model has been developed, which uses experimental engine data to estimate a realistic final recoverable energy. The model is able to evaluate the performance of each recovery subsection, highlighting interactions and possible trade-offs between them. Hence, the combined system can be optimized from a global point of view, identifying the most influential operating parameters and also considering a regeneration stage in the ORC unit.

On Combining Shape Memory Alloy Actuators and Pneumatic Actuators for Performance Enhancement in Soft Robotics

Through soft robotics, flexible structures confer an elevated degree of protection and safety in usage, as well as precision and reliability. Using theoretical models while combining different types of soft components opens a wide variety of possibilities for the development of new and better alternatives to rigid robots. Modeling and controlling soft robotic structures is still a challenge and is presented in different ways by the scientific community. The present scientific work aims to combine two of the most popular types of soft actuators, specifically shape memory alloy and pneumatic actuators. The purpose is to observe the interaction between individual entities and the resulting combined dynamics, highlighting the distinctive effects and influences observed in the combined system. An evaluation is conducted from a numerical simulation perspective in the MATLAB environment using representative mathematical models. The tests prove that a structure combining these particular actuators benefits from the advantages of both components and even compensates for individual downsides.

Integral Sliding Mode Disturbance Observer Based Preview Repetitive Control

Abstract This paper deals with the problem of integral sliding mode disturbance observer (ISDOB) based preview repetitive control (PRC) for a class of nonlinear systems subject to mismatched disturbances and nonlinearity. First, an ISDOB-based PRC law is presented to estimate and compensate the exogenous disturbances and nonlinearity. Next, by using a new equality constraint, a continuous-discrete two-dimensional(2D) system is established. Then, the stability of the combined controller-observer system is derived on the basis of a Lyapunov analysis, 2D system theory and the singular-value-decomposition (SVD) technique. By solving an LMI, the gains of the controller and state observer can be obtained. Finally, two numerical examples are provided to illustrate the effectiveness and superiority of the proposed method.

Numerical and experimental study of a suspension bridge with combined viscous-steel damping system under train and seismic loads

The longitudinal dynamic performance of long-span bridges with passive vibration control devices when subjected to vehicle and seismic loads has raised extensive attention of the civil engineering community. This study aims to provide numerical and experimental assessments of the dynamic performance of a railway suspension bridge with the Combined Viscous-Steel Damping System (CVSDS) under various excitations. The deck is simplified to a single-degree-of-freedom (SDOF) system according to the longitudinal vibration characteristics of the suspension bridge. The Dynamic Equation Method (DEM) and Fourier Expansion Method (FEM) are suggested for the equivalence of the spatiotemporal variable train loads to horizontal excitations. A simplified two-stage analytical model is proposed to simulate the restoring force characteristics and fuse-lock function of the CVSDS. Shake table tests are conducted to further illustrate the feasibility of the simplified model and evaluate the effectiveness of the CVSDS. The results indicate that the SDOF system is reasonable and satisfactory in simulating the deck displacement. The two-stage working mechanism of the CVSDS is verified by both the simulation and experiment, i.e. the viscous fluid damper works under train loads and the steel yielding damper operates under earthquakes. The vibration mitigation effectiveness of the CVSDS is remarkable.

Depolymerization of the polyester-polyurethane by amidase GatA250 and enhancing the production of 4,4'-methylenedianiline with cutinase LCC.

Polyurethane (PU) is a complex polymer synthesized from polyols and isocyanates. It contains urethane bonds that resist hydrolysis, which decreases the efficiency of biodegradation. In this study, we first expressed the amidase GatA250, and then, assessed the enzymatic characterization of GatA250 and its efficiency in degrading the polyester-PU. GatA250 degraded self-synthesized thermoplastic PU film and postconsumption foam with degradation efficiency of 8.17% and 4.29%, respectively. During the degradation, the film released 14.8µm 4,4'-methylenedianiline (MDA), but 1,4-butanediol (BDO) and adipic acid (AA) were not released. Our findings indicated that GatA250 only cleaved urethane bonds in PU, and the degradation efficiency was extremely low. Hence, we introduced the cutinase LCC, which possesses hydrolytic activity on the ester bonds in PU, and then used both enzymes simultaneously to degrade the polyester-PU. The combined system (LCC-GatA250) had higher degradation efficiency for the degradation of PU film (42.2%) and foam (13.94%). The combined system also showed a 1.80 time increase in the production of the monomer MDA, and a 1.23 and 3.62 times increase in the production of AA and BDO, respectively, compared to their production recorded after treatment with only GatA250 or LCC. This study provides valuable insights into PU pollution control and also proposes applicable solutions to manage PU wastes through bio-recycling.

The Energetics of the Lagrangian Evolution of Tropical Convective Systems

Abstract The convective life cycle is often conceptualized to progress from congestus to deep convection and develop further to stratiform anvil clouds, accompanied by a systematic change in the vertical structure of vertical motion. This archetype scenario has been developed largely from the Eulerian viewpoint, and it has yet to be explored whether the same life cycle emerges itself in a moving system tracked in the Lagrangian manner. To address this question, Lagrangian tracking is applied to tropical convective systems in combination with a thermodynamic budget analysis forced by satellite-retrieved precipitation and radiation. A new method is devised to characterize the vertical motion profiles in terms of the column import or export of moisture and moist static energy (MSE). The bottom-heavy, midheavy, and top-heavy regimes are identified for every 1° × 1° grid pixel accompanying tracked precipitation systems, making use of the diagnosed column export/import of moisture and MSE. The major findings are as follows. The Lagrangian evolution of convective systems is dominated by a state of dynamic equilibrium among different convective regimes rather than a monotonic progress from one regime to the next. The transition from the bottom-heavy to midheavy regimes is fed with intensifying precipitation presumably owing to a negative gross moist stability (GMS) of the bottom-heavy regime, whereas the transition from the midheavy to top-heavy regimes dissipates the system. The bottom-heavy to midheavy transition takes a relaxation time of about 5 h in the equilibrating processes, whereas the relaxation time is estimated as roughly 20 h concerning the midheavy to top-heavy transition.

An optimization of efficient combined cycle power generation system for fusion power reactor

Fusion power plants can meet the energy demands of the world. The high thermal performance of a power generation system is still a challenge and one of the developing trends with a fusion reactor due to the high outlet temperature. A combined cycle system has been optimized to work at high outlet temperature and pressure of fusion power reactor with thermal power of 2500 MWth and its input parameter has been optimized along with impact of partial load to achieve high thermal performance very first time. The combined cycle based on the concept of two stages of expansion in the closed-Brayton-cycle and two reheaters in the Rankine cycle named Schematic-IV with the higher thermal performance of 58.19% as compared to Schematic-I, II and III has been proposed for a fusion power reactor. The increase in more than one expansion stage and reheat stage is not economical because it increased the thermal performance by about half of performance as compared to one. The effect of isentropic efficiency of compressor and heat rate have been investigated to validate the thermodynamic model and calculations. The optimized thermal performance of the combined cycle is 58.19% at a feed water mass flow rate of 592 kgs−1 and steam outlet temperature of 277 °C in the combined cycle. The heat rate decreased and thermal performance increased with the mass flow rate verifying that the thermodynamic model is correct. The thermodynamic analysis of the combined cycle-based nuclear reactor provides insights for better system thermal performance and reveals the effect of key parameters on the system performance.

A technical-economic analysis of integrating vine prunings energy conversion systems for CHP production in local wineries

This study proposes the energy conversion of vine prunings to supply energy to local wineries, with a focus on the Riunite & CIV branch winery located in Carpi (Modena, Italy), exploring the possibility of generating both electricity and heat through biomass gasification. A Matlab-Simulink model is used to evaluate the energy savings that can be achieved when an energy storage system is coupled with the combined heat and power generation system. Within this context, the results showed that it is possible to save ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx $$\\end{document}30% of the electricity and ≈\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx $$\\end{document}60% of the thermal energy demanded by the winery. However, the economic viability of the project is hindered by high investment and operation costs. DPB is strongly affected by the cost of biomass and the energy prices, resulting in a profitable investment for electricity prices higher than 0.30 ÷>\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\div>$$\\end{document}0.57 €/kWh according to the different scenarios investigated.

Integrated Combined Heating, Cooling and Electricity System Based on Triple-Effect Free-Piston Stirling Configuration

Conventional combined cooling, heating, and power (CCHP) systems, involving multiple energy conversion technologies, are composed of a variety of coupled subsystems with different working principles. To solve the problems of bulky structure, operational complexity, and high initial investment cost, a novel integrated combined heating, cooling, and electricity system based on the same energy conversion technology with a triple-effect free-piston Stirling configuration was proposed. Compared with the traditional system, the novel integrated system can cool, heat, and generate power using one machine without introducing additional devices. Some verification experiments were tested on a built experimental platform to validate the feasibility of the concept of this configuration. The result shows that the system was able to obtain the highest values of COPc, COPh, and the output performance coefficient of 0.26, 1.28, and 1.54, respectively, which can save 39% of energy consumption compared with traditional independent energy-supplying systems when providing the same cooling and heating capacity and electricity under typical working conditions. It is expected that the reported result can facilitate a practical application in decentralized CCHP systems.