Changes In Design Parameters Research Articles

The impact of turbulence models and design parameters on solar chimney power plant efficiency: A CFD study

This study numerically examines the effects of chimney height, chimney radius and collector height on the velocity, pressure and temperature distribution in a Solar Chimney Power Plant (SCPP). The analyses were performed using ANSYS Fluent software with two different turbulence models (RNG k-ε and SST k-ω). The results show that increasing the chimney height significantly boosts the outlet velocity but decreases the outlet temperature. Conversely, as the chimney radius increases, the outlet velocity decreases and the outlet temperature slightly drops. Changes in collector height result in complex behavior for both turbulence models in terms of outlet velocity and temperature, highlighting the importance of an optimal collector height. The study includes detailed and numerical data on how different turbulence models can be used for performance analysis and optimization. According to the analysis results, increasing the chimney height from 100 meters to 200 meters resulted in a 35% increase in outlet velocity and a 20% decrease in outlet temperature in the RNG k-ε model. In the SST k-ω model, the same increase raised the outlet velocity by 30% and decreased the outlet temperature by 15%. The research showed that both RNG k-ε and SST k-ω turbulence models respond notably to changes in collector height and design parameters. The RNG k-ε model reacts more quickly and sensitively, while the SST k-ω model behaves more steadily.

Optimizing Microfluidic Channel Design with High-Performance Materials for Safe Neonatal Drug Delivery.

Designing the microfluidic channel for neonatal drug delivery requires proper considerations to enhance the efficiency and safety of drug substances when used in neonates. Thus, this research aims to evaluate high-performance materials and optimize the channel design by modeling and simulation using COMSOL multiphysics in order to deliver an optimum flow rate between 0. 3 and 1 mL/hr. Some of the materials used in the study included PDMS, glass, COC, PMMA, PC, TPE, and hydrogels, and the evaluation criterion involved biocompatibility, mechanical properties, chemical resistance, and ease of fabrication. The simulation was carried out in the COMSOL multiphysics platform and demonstrated the fog fluid behavior in different channel geometries, including laminar flow and turbulence. The study then used systematic changes in design parameters with the aim of establishing the best implementation models that can improve the efficiency and reliability of the drug delivery system. The comparison was based mostly on each material and its appropriateness in microfluidic usage, primarily in neonatal drug delivery. The biocompatibility of the developed materials was verified using the literature analysis and adherence to the ISO 10993 standard, thus providing safety for the use of neonatal devices. Tensile strength was included to check the strength of each material to withstand its operation conditions. Chemical resistance was also tested in order to determine the compatibility of the materials with various drugs, and the possibility of fabrication was also taken into consideration to identify appropriate materials that could be used in the rapid manufacturing of the product. The results we obtained show that PDMS, due to its flexibility and simplicity in simulation coupled with more efficient channel designs which have been extracted from COMSOL, present a feasible solution to neonatal drug delivery. The present comparative study serves as a guide on the choice of materials and design of microfluidic devices to help achieve safer and enhanced drug delivery systems suitable for the delicate reception of fragile neonates.

METHOD OF ASSESSING THE CHANGE IN DESIGN PARAMETERS OF PRECISION ROTARY SYSTEMS BY THE PHASE SHIFT OF THE VIBRATION STATE

The article examines the issue of precision rotary systems (PRS) and the relationship between their dissipative characteristics and changes in design parameters, which is applicable for assessing the quality of their assembly and diagnosing objects in general. We identified a dynamic model, the dissipative parameters of which sufficiently accurately reflect the local properties of the structure. The question of assessing the quality of assembly by dissipative parameters comes down to the choice of the diagnostic sign that is most suitable for this case and the method of its measurement. Such a sign is a phase shift between the disturbance force and the vibration velocity. From this point of view, phase-frequency measurement methods are generally more accurate, which allows using the advantages of precise hardware methods to obtain information to the fullest extent. The proposed variation ratio, which connects the changes in a real object’s phase vector of the mechanical impedance (PVMI) and the deviation of the dissipative parameters of its mathematical model, makes it possible to diagnose the dissipative parameters with a sufficient accuracy degree. The considered numerical example of a partial assembly of precision rotary systems confirms the accuracy of the calculation. Thus, the proposed variation ratio, which connects the changes in the PVMI of a real object and the deviation of the dissipative parameters of its mathematical model, allows for the diagnosis of the dissipative parameters with a sufficient accuracy degree. The considered numerical example of a partial assembly of the PRS confirms the accuracy of the calculation. This fact is of particular importance in manufacturing aviation and space technology products. We should also note that the existing analysis methods do not provide an opportunity to form an idea about the nature of the total measured signal and its structure. Therefore, the work solves the task of developing a method for diagnosing the controlled technical condition of a rotary electromechanical system based on the selection of the most informative ranges of the output signal to increase the reliability of diagnosis. Keywords: oscillatory system, dissipative properties, mathematical model, phase angle, impedance, sensitivity matrix.

METHOD OF ASSESSING THE CHANGE IN DESIGN PARAMETERS OF PRECISION ROTARY SYSTEMS BY THE PHASE SHIFT OF THE VIBRATION STATE

The article examines the issue of precision rotary systems (PRS) and the relationship between their dissipative characteristics and changes in design parameters, which is applicable for assessing the quality of their assembly and diagnosing objects in general. We identified a dynamic model, the dissipative parameters of which sufficiently accurately reflect the local properties of the structure. The question of assessing the quality of assembly by dissipative parameters comes down to the choice of the diagnostic sign that is most suitable for this case and the method of its measurement. Such a sign is a phase shift between the disturbance force and the vibration velocity. From this point of view, phase-frequency measurement methods are generally more accurate, which allows using the advantages of precise hardware methods to obtain information to the fullest extent. The proposed variation ratio, which connects the changes in a real object’s phase vector of the mechanical impedance (PVMI) and the deviation of the dissipative parameters of its mathematical model, makes it possible to diagnose the dissipative parameters with a sufficient accuracy degree. The considered numerical example of a partial assembly of precision rotary systems confirms the accuracy of the calculation. Thus, the proposed variation ratio, which connects the changes in the PVMI of a real object and the deviation of the dissipative parameters of its mathematical model, allows for the diagnosis of the dissipative parameters with a sufficient accuracy degree. The considered numerical example of a partial assembly of the PRS confirms the accuracy of the calculation. This fact is of particular importance in manufacturing aviation and space technology products. We should also note that the existing analysis methods do not provide an opportunity to form an idea about the nature of the total measured signal and its structure. Therefore, the work solves the task of developing a method for diagnosing the controlled technical condition of a rotary electromechanical system based on the selection of the most informative ranges of the output signal to increase the reliability of diagnosis. Keywords: oscillatory system, dissipative properties, mathematical model, phase angle, impedance, sensitivity matrix.

Design strategy for resonance avoidance to improve the performance of tension leg platform-type floating offshore wind turbines

The objective of this study is to determine the effect of elasticity of the tower and blades of a large tension leg platform (TLP)-type FOWT on the eigenmodes of the entire system and suggest reference directions to be implemented in the conceptual design stage. Typically, TLP-type FOWTs are connected by a mooring system with strong tension and exhibit an extremely short natural period of motion compared with a semi-submersible platform. Furthermore, the wind turbine tower mounted on the floating platform is flexible in the fore-aft and side-to-side directions, forming a vibrating system in itself; therefore, it is coupled with the motion of the floating platform. In particular, the tower elasticity is known to influence the roll and pitch motions of the platform. In this study, the motion response characteristics of the platform were investigated according to the changes in the tower design parameter (bending stiffness). The influence of blade elasticity was also confirmed, verifying that the physical characteristics of both the tower and blade significantly affect the motion of the TLP. Additionally, the degree of influence based on environmental loads was identified to suggest a design direction for FOWTs while avoiding resonance.

Repair Analysis of Overlay Woven Fabric CFRP Laminates

The increase in aerospace composites usage for structural components demands advanced repair analysis. Overlay repairs of carbon fiber-reinforced polymer laminates offer an alternative that is easier to perform and less time-consuming to produce than the widely used tapered scarf repair and stepped lap. Composite specimen manufacturing was based on both twill carbon/epoxy prepreg and wet lay-up. The repair was performed with both prepreg and wet extra plies to the parent prepreg structure. However, the design of overlay joints must be carefully investigated to avoid generating stress concentration regions at free edges. This study examined specific extra ply terminations' impact on peak stresses in the adhesive bond line. Linear finite element analysis was performed to conduct a maximum principal stress study with a focus on three joint design parameters: ply material, overply effect, and stacking sequence. FEA accurately predicted experimentally observed responses and provided further insight into the failure behavior of the structure. Results showed that overlay joints have a strong sensitivity to ply material type, the number of overply, and stacking sequence. The introduction of overplies provided protection and stiffness at joint tips, and an overply material behavior was identified. The location of 0̊ plies in the composite laminates was highlighted as an important factor. The analysis was then extended to three-dimensional FE models for verification. In conclusion, results showed that high-stress concentration in overlay joints can be mitigated with the introduction of overplies and appropriate changes in joint design parameters to reduce stress peaks at joint tips and corners.

A study on ice resistance prediction based on deep learning data generation method

Accurate prediction of ice resistance plays an important role in ensuring the safety of ship navigation when sailing in ice regions. This paper focuses on the design of a data generation deep learning model and an interpretable ice resistance prediction deep learning model. By selecting the appropriate ship, ice parameters and model experimental data to build the dataset, the influence of different data preprocessing methods on the model results are discussed. The processed data is expanded by Deep Convolutional Generative Adversarial Network (DCGAN). On this basis, a Graph Neural Network (GNN) is built to explain the distribution of network weights and the generalization effect of the model. The established model (GNN-DCGAN) and several ice resistance prediction methods are compared and analyzed. In addition, the design of polar ships needs to comprehensively consider the dynamic changes of ship design parameters and the mechanical properties of ice. In this paper, taking MT UIKKU as an example, the parameter sensitivity analysis is carried out to study the scope of application of the model and the contribution of different parameters. The results show that the DCGAN method can improve the prediction accuracy and application scope of GNN model. The predictions exhibit a high level of agreement with the experimental data, which can provide valuable references for the design of ship in ice regions.

Evaluation of the energy and exergy of a trans‐critical CO2 cycle driven by a double flash geothermal power plant

AbstractFacing the dual challenges of environmental impact and the finite nature of fossil fuels, the shift toward sustainable energy sources is imperative. Geothermal energy, a renewable and underutilized resource, offers a promising alternative. This study ventures into a novel domain, exploring the integration of trans‐critical CO2 (tCO2) cycle with a double‐flash geothermal (DFG) cycle, an area not extensively covered in existing research. This study aims to develop a recovery system that utilizes a tCO2 cycle powered by a DFG cycle. A crucial part of this study involves conducting a sensitivity analysis to evaluate the system's energy and exergy performance. This analysis focuses on understanding the impact of changes in key system design parameters, such as energy efficiency, exergy efficiency, net power output, and total exergy destruction rate, to determine the optimal values for these parameters. The results indicate that the recovery system shows a significant improvement of 22% in energy efficiency over the basic cycle. However, there is a decrease in exergy efficiency in the recovery system, which represents a 5.26% decline. As a result, this study paves the way for innovative approaches in geothermal energy use, suggesting potential breakthroughs in renewable technologies.

Assessment of a sustainable power generation system utilizing supercritical carbon dioxide working fluid: Thermodynamic, economic, and environmental analysis

Solar energy stands out as one of the most abundant and cost-effective resources for energy conversion systems, playing a pivotal role in addressing the world's growing energy demands and environmental concerns. This study focuses on a power generation system that integrates multiple technologies for efficient energy conversion, including a parabolic solar trough collector unit, a supercritical carbon dioxide Brayton cycle, and two dual-pressure organic Rankine cycles. The goal is to assess this system from various angles, including energy, exergy, exergoeconomic, and exergoenvironmental aspects. The base mode study results reveal an overall energy efficiency of 16.66 %, exergy efficiency of 17.88 %, a total net power generation of 17.32 MW, a payback period of 4.38 years, and a total exergoenvironmental impact rate of 126.75 Pt/h. Additionally, the study conducts a parametric investigation to analyze how the system performs under different conditions and how changes in design parameters affect its main outputs. Furthermore, the study utilizes a multi-objective particle swarm optimization algorithm and a decision-maker method to identify the most desirable condition for the system's performance. Three optimization scenarios are considered, and various specific costs for electricity are evaluated to determine the payback period and net present value.

Multi-Objective Optimization Design of FRP Reinforced Flat Slabs under Punching Shear by Using NGBoost-Based Surrogate Model

Multi-objective optimization problems (MOPs) in structural engineering arise as a significant challenge in achieving a balance between prediction accuracy and efficiency of the surrogate models, which are conventionally adopted as mechanics-driven models or numerical models. Data-driven models, such as machine learning models, can be instrumental in resolving intricate structural engineering issues that cannot be tackled through mechanics-driven models. This study aims to address the challenges of multi-objective optimization punching shear design of fiber-reinforced polymer (FRP) reinforced flat slabs by using a data-driven surrogate model. Firstly, this study employs an advanced machine learning model, namely Natural Gradient Boosting (NGBoost), to predict the punching shear resistance of FRP reinforced flat slabs. The comparisons with other machine learning models, design provisions and empirical theory models illustrate that the NGBoost model has higher accuracy in predicting the punching shear resistance. Additionally, the NGBoost model is explained with Shapley Additive Explanation (SHAP), revealing that the slab’s effective depth is the primary factor affecting the punching shear resistance. Then, the formulated NGBoost model is adopted as a surrogate model in conjunction with the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) algorithm for multi-objective optimization design of FRP reinforced flat slabs subjected to punching shear. Through a case study, it is demonstrated that the Pareto-optimal set of the punching shear resistance and cost of the FRP reinforced flat slabs can be successfully obtained. By discussing the effects of design parameter changes on the results, it is also shown that increasing the slab’s effective depth is a relatively effective way to achieve higher punching shear resistance of FRP reinforced flat slabs.

Enhancing single-mode guidance using avoided crossings in anti-resonant hollow-core fibers with five nested cladding tubes

We numerically analyze the nested anti-resonant nodeless fibers (NANFs) with five tubes to determine the best single-mode guidance and low confinement loss for the fundamental mode simultaneously. We derive the empirical relation between structural parameters that lead to avoided crossings between the core higher order modes (HOMs) and the cladding tube modes in a 5-tube nested design to achieve robust single-mode guidance. We report a low confinement loss of 1.17×10−3 dB/km and 0.23 dB/km, and huge HOM extinction ratio (HOMER) of the order of 105 and 104 at wavelengths of 650 nm and at 1550 nm respectively. We also investigate the fabrication tolerances of the confinement loss and HOMER to the changes in design parameters. These 5-tube NANFs exhibit a broad loss spectrum of 200 nm with loss of fundamental mode ¡ 0.003 dB/km and HOMER of 16000 centered around 650 nm. NANFs find applications in quantum communications, sensing and telecommunications and this work can be helpful in design optimization of such fibers.

Development of energy efficient design proposals for air conditioned mosques: Temperate humid climate case

Mosques, which are types of religious buildings, are large buildings where many people pray at the same time. The diversity of the user type and density and the variability of the usage schedule make it difficult to establish the homogeneous thermal comfort of these large-volume public buildings. At the same time, the energy consumption in the buildings should be minimal in nowadays when the conventional energy sources decrease. The aim of this study is to evaluate created design strategies for designers and users in order to minimize energy consumption by determining the passive design criteria and choosing the type of air conditioning equipment while providing an acceptable thermal comfort level in mosques. According to the method created for the aim, the scenarios of mosques were compared in terms of thermal comfort and energy consumption in the temperate humid climate conditions. This method includes the analysis of scenarios created from the change of design parameters of mosques (plan, size, roof type of the mosques) with a simulation software which was validated with actual utility data. The suggestions were presented for the selection and design of the mechanical system as a result of the implementation of the created method. When the design scenarios of mosques are compared, the air conditioning of the indoor with radiant method consumed less energy than HVAC equipment with fan system. In accordance with the plan schemes (square, rectangle, circular), the least energy consumption per unit area was in the circular plan scheme and hemispherical design. Compared to the roof types (single dome, multi dome, pyramidal roof, flat roof), the most energy consumption per unit area was generally in the multi dome design. According to the average energy consumption values of the HVAC systems, there was 23 % less energy consumption in the flat plan type (105.06 kWh/m2) compared to the rectangular plan type (129.2 kWh/m2). In the intermittent use schedule of the HVAC system, 8 % more energy was consumed than in the continuous use schedule. According to the air changes per hour in the mosques, there was 5.93 % more energy consumption in 2 ach conditions compared to 0.5 ach conditions.

Exergy-based methodology to develop design guidelines for performance optimization of a coupled co-axial thermoacoustic refrigerator

Performance of thermoacoustic (TA) systems are very complex, and their performance optimization is a difficult task, and most TA systems have relatively very low efficiencies. The main objective of this study was to develop an exergy analysis to introduce a guide for a designer, how to optimize the performance of a TA system. We have applied this methodology to a coupled thermoacoustic engine and refrigerator with a standing wave in the engine and a traveling wave in the refrigerator. In an optimization procedure, a lumped systems numerical analysis was performed to predict the main parameters of the thermoacoustic system. The numerical method was validated by comparison with numerical and experimental results in the literature. The cost function was the total system coefficient of performance, and design parameters include the refrigerator regenerator length, location, and hydraulic radius. The performance index was decomposed into three main subsystem indices, i.e., the efficiency of the engine, the efficiency of the resonator, and the coefficient of performance of the refrigerator. The optimum point for each component was found, and the total system optimal point which is a result of thermoacoustic interaction of all segments were analyzed. It was illustrated how a change in design parameters could affect the pressure and velocity amplitude and phase distribution in different subsystems, which help the designer deal with the challenge of the optimal parameter selection to enhance the system performance. Finally, an exergy analysis was introduced to assess loss mechanism's contribution to each refrigerator's component. This result in a roadmap for optimization of the system. A new parameter called non-dimensional exergy loss portion (NELP) was introduced, which may significantly show the improvement potential in each system component.

Analysis of Structural Parameters of Steel-NC-UHPC Composite Beams.

The cracking of the negative moment area of steel-normal concrete (NC) composite bridges is common owning to the low tensile strength of concrete. In order to solve the problem, Ultra High Performance Concrete (UHPC) is used to enhance the tensile performance of the negative moment area. This paper conducted interface experiments to study the bonding behaviour of the UHPC-NC interface. The design parametric analysis of steel-NC-UHPC composite bridges was carried out based on the interface experimental results. Firstly, slant shear tests and flexural shear tests were carried out to study the rationality of the interface handling methods. Then, the finite element model was used to analyze the state of every component in the composite beams based on experimental results, such as the stress of UHPC, concrete and steel plate. Finally, the calculation results of finite analysis were compared and summarized. It is concluded that (1) the chiseling interface can meet the utilization requirements of physical bridges. The average shear stress and flexural tensile strength of the chiseling interface are 10.29 MPa and 1.93 MPa, respectively. In the failure state, a slight interface damage occurs for specimens with a chiseling interface. (2) The influence on overall performance is different for changes in different design parameters. The thickness of concrete has a significant influence on the stress distribution of composite slabs. (3) Reliable interface simulation is conducted in the finite element models based on interface test results. The stress variation patterns are reflected in the change of design parameters.

Cutting-Edge Analytical and Numerical Approaches to the Gilson–Pickering Equation with Plenty of Soliton Solutions

In this paper, the Gilson–Pickering (GP) equation with applications for wave propagation in plasma physics and crystal lattice theory is studied. The model with wave propagation in plasma physics and crystal lattice theory is explained. A collection of evolution equations from this model, containing the Fornberg–Whitham, Rosenau–Hyman, and Fuchssteiner–Fokas–Camassa–Holm equations is developed. The descriptions of new waves, crystal lattice theory, and plasma physics by applying the standard tan(ϕ/2)-expansion technique are investigated. Many alternative responses employing various formulae are achieved; each of these solutions is represented by a distinct plot. Some novel solitary wave solutions of the nonlinear GP equation are constructed utilizing the Paul–Painlevé approach. In addition, several solutions including soliton, bright soliton, and periodic wave solutions are reached using He’s variational direct technique (VDT). The superiority of the new mathematical theory over the old one is demonstrated through theorems, and an example of how to design and numerically calibrate a nonlinear model using closed-form solutions is given. In addition, the influence of changes in some important design parameters is analyzed. Our computational solutions exhibit exceptional accuracy and stability, displaying negligible errors. Furthermore, our findings unveil several unprecedented solitary wave solutions of the GP model, underscoring the significance and novelty of our study. Our research establishes a promising foundation for future investigations on incompressible fluids, facilitating the development of more efficient and accurate models for predicting fluid behavior.

Intelligent Optimization Design of Distillation Columns Using Surrogate Models Based on GA-BP

The design of distillation columns significantly impacts the economy, energy consumption, and environment of chemical processes. However, optimizing the design of distillation columns is a very challenging problem. In order to develop an intelligent technique to obtain the best design solution, improve design efficiency, and minimize reliance on experience in the design process, a design methodology based on the GA-BP model is proposed in this paper. Firstly, a distillation column surrogate model is established using the back propagation neural network technique based on the training data from the rigorous simulation, which covers all possible changes in feed conditions, operating conditions, and design parameters. The essence of this step is to turn the distillation design process from model-driven to data-driven. Secondly, the model takes the minimum TAC as the objective function and performs the optimization search using a Genetic Algorithm to obtain the design solution with the minimum TAC, in which a life-cycle assessment (LCA) model is incorporated to evaluate the obtained optimized design solution from both economic and environmental aspects. Finally, the feasibility of the proposed method is verified with a propylene distillation column as an example. The results show that the method has advantages in convergence speed without sacrificing accuracy and can obtain an improved design solution with reduced cost and environmental impact. Compared with the original design using rigorous simulation, the TAC is reduced by 6.1% and carbon emission by 27.13 kgCO2/t.

Multi-objective optimization of a hybrid energy system integrated with solar-wind-PEMFC and energy storage

The move towards achieving carbon neutrality has sparked interest in combining multiple energy sources to promote renewable penetration. This paper presents a proposition for a hybrid energy system that integrates solar, wind, electrolyzer, hydrogen storage, Proton Exchange Membrane Fuel Cell (PEMFC) and thermal storage to meet the electrical and heating demands of a student dormitory in Shanghai. The proposed system is optimized to simultaneously account for multiple objectives, including economy, environmental benefits, and grid interaction, measured by Equivalent Annual Cost (EAC) for the life cycle of 20 years, Primary Energy Saving Ratio (PESR) of the heating system and Grid Interaction Level (GIL) of the electrical system. The effectiveness of the optimization results from NSGA-II is verified and compared with MOPSO to determine the optimal installation configuration and operation strategies. The results highlight the significance of energy storage in enabling greater renewable integration and the potential of hydrogen to play a vital role in the transition to a low-carbon economy. The optimal design of the proposed hybrid system can meet the power and heat demand of a student dormitory with a floor area of 2679m2. The Pareto-optimal solutions of PESR and GIL for NSGA-II fall within the range of (89 %, 104 %) and (70 %, 88 %), respectively. A significant number of Pareto-optimal solutions cluster around an EAC of approximately 160 k RMB. The optimization by MOPSO exhibited the similar results. Additionally, the sensitivity analysis provides insights into the sensitivity of objectives to changes in optimal design parameters, facilitating the design and optimization of similar hybrid energy systems integrated with a closed loop for hydrogen production and utilization in the future.

A New Method for Selecting the Geometry of Systems for Surface Infiltration of Stormwater with Retention

The application of infiltration basins and tanks is one of the primary means of sustainable stormwater management. However, the methods currently used to size these facilities do not take into account a number of parameters that have a significant impact on their required capacity. In light of this, the aim of this research was to develop a new method for selecting the geometry of the infiltration basins and tanks. Its application in the initial phase of designing stormwater management systems will allow assessing the validity of using such facilities in a given catchment area. This paper also presents the results of local and global sensitivity analyses examining how changes in individual design parameters influence stormwater infiltration facilities. The effectiveness of the developed model was evaluated through the example of a real urban catchment. The study was based on a hydrodynamic analysis of more than 3000 model catchments. The research plan was developed using Statistica software. On the other hand, the analysis of the results of hydrodynamic simulations was made possible through the use of artificial neural networks designed using the Python programming language. The research also confirmed that parameters such as the total catchment area, the percent of impervious area, and the type of soil within the catchment are crucial in the design process of these facilities. The results of this research can be considered when designing infiltration basins and tanks under Polish conditions. The described algorithm can also be used by other researchers to develop similar models based on different rainfall data. This will contribute to increasing the safety of urban infrastructure.

Learning to learn by using nonequilibrium training protocols for adaptable materials

Evolution in time-varying environments naturally leads to adaptable biological systems that can easily switch functionalities. Advances in the synthesis of environmentally responsive materials therefore open up the possibility of creating a wide range of synthetic materials which can also be trained for adaptability. We consider high-dimensional inverse problems for materials where any particular functionality can be realized by numerous equivalent choices of design parameters. By periodically switching targets in a given design algorithm, we can teach a material to perform incompatible functionalities with minimal changes in design parameters. We exhibit this learning strategy for adaptability in two simulated settings: elastic networks that are designed to switch deformation modes with minimal bond changes and heteropolymers whose folding pathway selections are controlled by a minimal set of monomer affinities. The resulting designs can reveal physical principles, such as nucleation-controlled folding, that enable such adaptability.

Thermodynamic investigation of variable‐speed compression unit in near‐isothermal compressed air energy storage

AbstractIsothermal compression is the state‐of‐the‐art in compressed air energy storage (CAES) technology. The study of cyclic pressurization unit in isothermal CAES is carried out in this paper. The unit can continuously compress air utilizing double vessels operating alternately. In each vessel, the large heat capacity of water and spray cooling is applied to establish a conducive environment for the air achieving the effect of efficient near‐isothermal compression. The operating mode of the cyclic pressurization unit is divided into sliding‐pressure operation and constant‐pressure operation according to the pressure of its outlet. By adopting the characteristic curves of pump, the dynamic model is built for the unit in this paper. Further, the differences between the cyclic pressurization unit in isentropic process and in variable‐speed process are quantified and compared in four different cases. In isentropic process, the energy‐saving ratio and exergy efficiency of the unit are expected to reach 20.4% and 95.0%, respectively. In variable‐speed process, the energy‐saving ratio and efficiency of the unit can achieve 7.3% and 73.4%, respectively. This gap is mainly determined by the off‐design performance of the pump. Moreover, the vessel volume should be no less than 3 m3 and 5 m3 when there is spraying and when there is no spraying. Furthermore, spraying favors the improvement of the worsened compression performance caused by the change of design parameters. The energy‐saving ratio can be improved via spraying by 1.3% to 11.0% and 1.8% to 25.6% in the isentropic and variable‐speed processes, respectively. Meanwhile, the exergy efficiency can be increased by 1.5% to 9.4% in the isentropic process and 1.4% to 8.4% in the variable‐speed by spraying.