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On-orbit manufacturing can reduce the cost and time needed by space exploration missions because in-situ maintenance activities can be achieved without the need for additional launches. Furthermore, recent developments in materials science in terms of better mechanical and thermal performance have allowed this application to become a potential reality. However, the deployment of on-orbit manufacturing presents several challenges, including the lack of convective heat transfer and human intervention. This paper proposes an on-orbit 3D printing device capable of operating at a temperature up to 400°C in the vacuum environment. To validate its feasibility for on-orbit manufacturing, we designed four extruders with different characteristics. We investigated the temperature profiles across the extruders under the vacuum condition through a heat transfer model. Based on the thermal analysis, a thermal control method, which combines the Proportion (P) and Fuzzy Proportion and Integration (Fuzzy PI) strategies, is designed to regulate the 3D printing device operation. With the extrusion rate of 8654.6 mm3 /h and the printing temperature at 400°C, the melting and solidification status of the PEEK (Polyether ether ketone) material is verified.

In this study, a new hybrid solar preheating intercooled gas turbine (SP-IcGT), is presented, in which a parabolic trough solar technology is used to preheat the compressed air before entering the combustor. The performance of the new hybrid gas turbine was evaluated and compared with the conventional hybrid solar preheating gas turbine (SP-GT). Several performance indicators were used in the analysis under Guangzhou (China) weather data. It is observed that the SP-IcGT is superior to the SP-GT system as it can boost the fuel-based efficiency by 19.35% versus 0.26% for the SP-GT system. In addition, the SP-IcGT has a much lower specific fuel consumption (about 7017 kJ/kWh) compared with the 10362 kJ/kWh for SP-GT. The highest fuel-based efficiency of 51.4% is obtained for the SP-IcGT with 47.4% improvement over the SP-GT, which exhibits a levelized electricity cost of 4.58 US/kWh. Meanwhile, fuel consumption and greenhouse gas emissions can be reduced greatly by integrating solar energy with the intercooled gas turbine. The SP-IcGT is more economical than applying carbon capture to the equivalent conventional gas turbine plant combined while achieving the same reduction of CO2 emissions. Overall, the SP-IcGT is an attractive system under different climates.

This research addresses the global Mittag-Leffler stability and synchronization control problems of the fractional-order memristor-based neural network, which more accurately describes physical phenomena than integer-order networks system, and simultaneously exhibits complex dynamic behaviors. Specifically, the difficulties due to the processing of derivatives and inequalities of the fractional-order memristor have overcome these issues via fractional differential inclusion, set-valued mapping, and a new Lyapunov functional. Furthermore, the state feedback controller has been designed to flexibly solve the complex system external disturbance, which involves a generalized type of proportional time-delay control law that enables flexible parameter adjustment.Obtained the results demonstrate better exponential stabilizable and asymptotic synchronization over traditional integer-order neural networks. They are also a generalization and promotion of the predecessors on the dynamic behavior analysis of complex systems. Finally, the validity of the theoretical results has been verified by simulation examples.

Although a thermoelectric device (TED) sub-cooler can improve the trans-critical carbon dioxide (TCO2) cycle, the maximum heating capacity by a single TED is limited by its internal properties. This paper integrates two serially connected and independently powered TED sub-cooler devices into the trans-critical carbon dioxide (TCO2) cycle to achieve a better share of the total heating capacity amongst the TED sub-coolers. A multi-objective optimization approach is used to further optimize this new TCO2+2-TED cycle in terms of coefficient of performance (COP) and system size. A capital cost analysis is also conducted to prove that this implementation is economically feasible. In the analysis, the effect of the number of thermoelectric modules, the heating capacity ratio between the two TED sub-coolers, and the type of thermoelectric module have been studied. Furthermore, both the water heating and refrigeration case studies have been separately studied by using the NSGA-II algorithm. Results show that, in both cases, only one unique solution out of 50 in the Pareto front registered the TCO2+2-TED cycle, which offered a further 6.24% COP improvement for water heating over the common TCO2+TED cycle solutions. The TED sub-cooler costs 20% of the compressor, so the solution is reasonably economical.

The free-flying space manipulators present challenges in controlling the motions of both the spacecraft bus and the manipulator, because of the highly-coupling system dynamics and the unknown space environment disturbances. Although the sliding mode controllers are robust to the unknown disturbances and system uncertainties, the chattering effect could affect the pointing accuracy and the lifetime of the actuators. This paper first introduces the dynamics of a CuBot, which is a 3-rigid-link manipulator based on the CubeSat platform. To maintain the robustness while decreasing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. To maintain the robustness while reducing the chattering effect, an innovative reinforcement learning based fuzzy adaptive sliding mode controller is proposed. The switching gain is updated to estimate the lumped upper bound of the system uncertainties and the unknown disturbances, and then a new fuzzy logic adaptive law is applied on the switching gain to decrease the chattering effects. On top of that, the fuzzy logic rules are tuned by an innovative modified reinforcement learning mechanism to achieve the better tracking performance. The uniformly ultimately bounded tracking errors are guaranteed by the proposed control scheme, and the effectiveness is validated by the simulation results.

A coupled analysis of agent behavior and Computational Fluid Dynamics (CFD) model is applied to investigate the fire evacuation effectiveness in a popular metro station in Guangzhou, China. Due to the high density and complexity of traffic, the concept of Required Safe Escape Time and Available Safe Escape Time (RSET/ASET), which is more flexible and adaptable than the “6 minutes” principle, is applied in the safety assessment of fire evacuation. To pursue a stable simulation of the coupled model, the standard Critical Radiant Flux is used to deter the tenability criteria for exposure to fire and heat. Various related factors, including the fire location, the Heat Release Rate (HRR) of fire, the crowd density, and the operation mode of escalators, are analyzed through a series of simulations. Results indicate that the interaction between fire and humans should not be neglected in the evacuation simulation. Both the fire location and the crowd density have a significant effect on the evacuation, while the HRR of fire has a minor impact. When the accident happens at the entrance of an escalator, RSET is 58.3% longer than that when the accident occurs in the middle of the platform. RSET grows with the increase of the crowd density linearly. Besides, the evacuation efficiency could be partly improved by changing escalators that usually operate in the descending mode into ascending mode.

This paper presents a new adaptive small chattering sliding mode control (SCSMC) scheme that uses reinforcement learning (RL) and time-delay estimation (TDE) for the motion control of free-floating space robotic manipulators (FSRM) subject to model uncertainty and external disturbance. The proposed sliding mode control scheme can achieve small chattering effects and improve the tracking accuracy by using a new adaptive law for the switching gain and a RL-based robust term to handle the control inputs. In SCSMC, the complicated multiple-input-multiple-output (MIMO) uncertain system of FSRM is transformed into multiple single-input-single-output (SISO) known subsystems with bounded estimation errors by the TDE technique and state feedback compensation. Subsequently, once the sliding variable is inside the designed manifold, the derivative of the switching gain for each subsystem becomes a negative hyperbolic tangent function of the associated sliding variable, which offers the ability to reduce chattering by decreasing the switching gain. Moreover, the RL based robust term for each subsystem is designed to avoid the loss of tracking accuracy caused by the aforementioned switching gain drop. The tracking errors are proven to be uniformly-ultimately-bounded (UUB) with an arbitrarily small bound by using the Lyapunov theory. The effectiveness of the proposed control scheme is verified by numerical simulations.

Although the Peltier sub-cooled trans-critical CO2 cycle concept has been applied for refrigeration, which typically involves discharging the heat into ambient air, this system is rarely considered for heat pumping purposes. Therefore, this research aims to expand the scope of the Peltier sub-cooled trans-critical CO2 cycle into heat pump water heating where the generated heat is uniquely discharged into water at temperatures progressively higher than ambient. The heat flows between the CO2 and flowing water are modelled as Nusselt based convective heat transfers where a 1D model is imposed to the direct gas cooler to improve simulation accuracy. Moreover, important but often neglected characteristics such as Peltier device size and Peltier heating factor (PHF) will also be analyzed. Results indicate that the PHF has an extremely strong influence on the overall system’s coefficient of performance (COP). Specifically, an optimal PHF value exists as a trade-off between the benefit of sub-cooling and the losses due to reduced CO2 mass flow rate, the latter of which caused reductions in the convective heat transfer coefficient and the direct gas cooler’s heating capacity. In the meantime, although larger Peltier device sizes improves the system COP, the improvement will converge towards a specific maximum.

Although implementations of CPVs to support electrolysis to produce hydrogen have recently been established, they often neglect the heat component which is important to improve electrolysis efficiency. Therefore, this research proposes to integrate the vapor compression cycle to concentrated photovoltaic panels to form a combined heat and power system that efficiently supplies such required energy to a water electrolyzer to produce hydrogen. The vapor compression cycle is modified to selectively choose whether the waste heat should support water heating or be discharged into the ambient environment where the latter method is aimed to save power consumption. A preliminary investigation of the proposed system is conducted by analyzing a commercial concentrated photovoltaic panel and simple formulations such as the theoretical Carnot efficiency for the vapor compression cycle. Results suggest that the required compressor power in the vapor compression cycle is very substantial and caused the effective electrical efficiency to drop from 40% to 10% for condenser temperature of 360 K–410 K. Fortunately, the heat available by the vapor compression cycle is much higher than that demanded by water electrolysis. Thus, the modified vapor compression cycle with the selective heat discharge functionality has demonstrated hydrogen production rate improvements of up to 4%.

This research conducts a thermodynamic and transient analysis of the hybrid concentrated photovoltaic panel and vapour compression cycle thermal (CPV-VCC/T) system that is designed for combined heat and power purposes. The model includes both the VCC’s thermodynamic model and the evaporator (CPV side) heat exchanger’s convective heat transfer effect. Various commercial refrigerants (R123, R22, R245fa and R134a) are analyzed where their performances are assessed in terms of coefficient of performance (COP) and the CPV’s resulting operating temperature. After the comparative steady state analysis, the CPV-VCC/T system is then tested in a two-day transient simulation involving varying irradiances and hot water demands. Steady state results demonstrate that the COP efficiency relative to Carnot will generally decrease as the condenser temperature increases. Also, although refrigerants R134a and R22 yielded up to 12% higher static COPs than R245fa and R123, the yielded electric energy gain from the two-day transient simulation is different by no more than 1.5%. Positively, the CPV-VCC/T system is found to yield 35% more electric energy than the conventional electric heating system. Although the CPV-VCC/T system yielded 5% less electric energy than direct water cooling, the CPV temperature was successfully maintained at 330 K as opposed to over 380 K.

Fuel cell based combined heat and power systems (FC-CHP) are a promising technology which can provide efficiently both electrical power and heat to residential and industrial consumers. However, FC-CHP system are typically complex in nature where much of the complexity arises from the necessary subsystems to operate the FC itself. This paper proposes a cost effective experimental emulator that acts like a real FC-CHP system by generating its key output characteristics while avoiding the complex component design of the real system. It achieves this by using two separate electrical circuits – One known as the Heat Emulator (HE) to emulate the waste heat characteristics and another, known as the Electric Power Emulator (EPE) to emulate the electrical power generation. Both circuits involve a controllable voltage source and a resistive load. A digital controller is then pre-programmed with an accurate FC model and its role is to control the source voltage and/or load resistance in the HE and EPE circuits such that these two circuits generate accurately the FC stack’s output characteristics. The HE circuit and a liquid cooling system is specifically implemented and water temperature control is used to study this system’s thermal efficiency.

While the integration of the fuel cell (FC) and the semiconductor thermoelectric device (TED) to form a clean energy hybrid FC-TED system has been previously studied using 0-D mathematical equations, a 3-D finite element model that couples together the physics between the two devices is yet to be comprehensively studied. This paper introduces a 3-D finite element model developed in COMSOL Multiphysics that simulates both the FC and the TED subsystems where the FC electrochemical dynamics and the TED's thermoelectric effect and heat transfer physics take place between them. The studied FC stack is in direct contact with one side of the TED via the top of the gas channel structure and the other side is then convectively cooled by active air cooling. Results demonstrate that the proposed model can easily simulate the TED as both a thermoelectric generator (TEG) or as a Peltier device for cooling and heating. In the TEG mode, energy harvesting efficiency is observed at only 0.1% but expected to improve with better TED to FC relative sizing. The Peltier heating mode is also found to be advantageous in terms of quickly regulating the FC stack temperature, a valuable feature for startup processes.

Although FC based electric buses are currently popular on urban streets or in short transit routes within large facilities, the version that is designed to operate on a highway, which has much higher dynamic requirements, is yet to be well developed. This research proposes to adopt the NSGA-II based multi-objective optimization scheme to optimize a fuel cell-battery-supercapacitor (SC) based FC power system (FCPS) that is specifically for a FC electric bus operating on the highway fuel economy cycle (HWFET). The optimization objectives are to minimize the FC's fuel consumption, the required battery and SC size and the battery degradation rate. More importantly, the optimization scheme is based on a combined energy management strategy (EMS) software parameter and hardware component sizing approach which is important for guaranteeing dynamically stable responses. This characteristic is achieved by imposing constraints that limit the transient time responses the DC-Bus capacitor voltage electrical parameters upon a generic step change in load power. Results demonstrate that dynamic stability can be guaranteed with proper software parameter and hardware components combinations without any trade-off requirements with the optimizer objectives. Moreover, the system mass and the battery degradation objectives are in trade-off but don't have any dependence to hydrogen consumption.

The combined heat and power system is a highly efficient energy source for many applications because heat and power are often of high demand. Although fuel cells and thermoelectric generators are popularly known to be used separately for combined heat and power purposes, there is little research on combining these two components for this application. This research proposes to analyze the hybrid fuel cell and thermoelectric system specifically when it is used as a combined heat and power system – thus forming a newly proposed fuel cell and thermoelectric combined heat and power (FC-TE-CHP) system. The key idea is to use the thermoelectric device to further improve the exergetic and temperature performance of the conventional fuel cell based combined heat and power (FC-CHP) system. Both systems are analyzed and compared by using a steady state thermodynamic model from both the temperature and exergetic perspectives. The exergetic efficiency and temperature results are reported by performing parametric sweeps of several key parameters such as fuel cell stack electric power, operation in thermoelectric cooler mode, water mass flow rate and radiator air convection coefficient. Subsequently, recommendations on how the FC-TE-CHP system can be operated efficiently in terms of exergy are drawn.

The thermoelectric (TE) device enables a conversion interface between the heat transfer and the electricity domain. Heat can be converted to electricity via the thermoelectric generator (TEG) effect and conversely, electricity can be converted to heat via the thermoelectric cooling (TEC) effect. In the meantime, varying the flow rate of coolants in a liquid cooling system is another common technique that is used to achieve temperature control. This paper proposes a fuzzy logic controller (FLC) that integrates both the combined TEG-TEC control method and the variable coolant rate techniques to achieve both the active temperature control (in TEC mode) and the energy harvesting capability (in TEG mode) of the TE device. The most significant control objectives are that the TEC mode is used to improve the temperature transient response whereas the variable coolant flow rate’s purpose is to drive the system towards operating in the TEG mode. Temperature control of a fuel cell stack is chosen as example study application and an experimental verification involving a heat emulator is presented to highlight the positive influence of the variable flow rate technique for improving the temperature transient and increasing the energy harvesting capability of the TEG-TEC control technique.

The thermoelectric (TE) device enables a conversion interface between the heat transfer and the electricity domain. Specifically, it can operate bi-directionally – Heat can be converted to electricity via the thermoelectric generator (TEG) effect and conversely, electricity can be converted to heat via the thermoelectric cooling (TEC) effect. As to date, most publications deal with the optimization of the TE device either in terms of the TEG performance or in terms of the TEC performance. This paper brings the two design approaches together to form a multi-objective optimization of the TE device. By performing such an optimization, the relationships between the TEG and TEC performance criterion are better established with key factors including any potential trade-off situations and possibilities for optimal design towards both objectives. Moreover, the key parameters that have the strongest influence on these criteria and the related trends are identified. Optimization results indicate that there is a strong correlation between the TEG performance and system mass but the correlation is less effective from the TEC perspective. On the other hand, the constraint requirements on the TEG design is found to have strong influence on the optimality of the TEC solutions.

The thermoelectric (TE) device enables a conversion interface between the heat transfer and the electricity domain. Specifically, it can operate bi-directionally – Heat can be converted to electricity via the thermoelectric generator (TEG) effect and vice versa via the thermoelectric cooling (TEC) effect. In most state of the art research, the TE device is operated either in the TEG mode or TEC mode but very seldom in both modes for a single control objective. This paper proposes a thermal management system for a fuel cell who exploits the bi-directional characteristics of the TE device to achieve both temperature control and the possibility for energy harvesting when active control is not required. The studied scenarios involve a time-based simulation involving heat generation levels that are typical of a 500 W rated operating proton exchange membrane fuel cell (PEMFC). The overall dynamic system is simulated using Simscape library components in Simulink and the controller itself is implemented using MATLAB s-functions. An experiment involving electric heaters to emulate the fuel cell’s body heat is also conducted to verify the proposed combined TEG-TEC control approach.

As a clean power system with a narrow temperature range of typically 60–95 °C, the low temperature (LT) proton exchange membrane fuel cell (PEMFC) requires an effective thermal management system to enhance its efficiency and durability. This paper focuses on a genetic algorithm based optimization of the thermoelectric generator (TEG) as applied to the PEMFC system. The genetic algorithm approach is advantageous over similar previous research in that it enables multi-objective optimization where the various TEG module parameters can be configured towards critical objectives such as maximum output power, minimal mass and maintaining the PEMFC within its operating temperature range. A second case study is also studied where the combined efficiency of the PEMFC and TEG is selected as an objective in replacement of the maximum TEG output power. Optimization results suggest that, in both cases, there is a trade-off situation between maximum output TEG power or maximum system efficiency with respect to system mass. It is also shown that the most important benefit of increasing the cooling convection coefficient is that it increases the system’s specific power where the heat sink areas can be smaller to achieve the same cooling rate.

Recently, combining the absorption chiller and dehumidifier is a well-favored implementation for high-quality air cooling. However, the coefficient of performance of the absorption chiller is limited because of the low-grade input energy, and in most previous works, the dehumidifier's energy requirement is independently supplied by solar energy or other high-grade energy. This paper addresses these problems by utilizing the condenser waste heat of the absorption chiller for dehumidification, which is achieved by regenerating a desiccant solution. A mathematical model of the absorption chiller and dehumidification was developed in MATLAB. Here, the energy, exergy value of the absorption chiller outputs is first analyzed with respect to the varying desiccant regeneration temperature, which shows that the condenser waste heat contains significant amounts of useable exergy. Then, an energy, exergy, and technical analysis of the dehumidifier and subsequently the coupled system reveals that utilizing the proposed integrated concept could greatly increase the air-cooling exergy efficiency from a conventional 6%–14%. This was achieved by setting the regeneration temperature to be at least 6 °C above ambient. Overall, the waste heat utilization concept enabled a more efficient building space cooling and dehumidification system than conventional multi-energy complementary systems in hot and humid climates.

Solar heating (SH) and radiative cooling (RC) have been regarded as promising clean techniques for thermal energy harvesting and temperature control. However, SH and RC are only a single function of heat collection and dissipation, which means the static device of SH and RC cannot meet the dynamic heat requirement of real-world applications, especially in the daytime. Here, a strategy of dynamic integration of SH and RC is proposed for tunable thermal management. A device (i.e., SH/RC device) that includes a silica cavity, ultrapure single-walled carbon nanotubes (SWCNTs) aqueous dispersion, solar reflective film, and deionized water is designed and fabricated. The outdoor experimental results show that the SH/RC device with SWCNTs media can effectively achieve heat collection with a maximum temperature of 78.9°C, while the SH/RC device with deionized water can achieve heat dissipation. Besides, the temperature modulation ability of the SH/RC device is tested to be 26.3°C and can be theoretically improved to be 60.3°C by improving the solar absorptivity (i.e., 0.9 for SH mode and 0.1 for RC mode) regulation ability of the device and improving its thermal emissivity (i.e., 0.9). Furthermore, annual analysis indicates that the cumulative time in which the SH/RC device temperature is in a comfortable region (i.e., 20°C-26°C) for humans is 60.9% and 30.3% higher than that of the device with individual SH and RC mode. In summary, this work provides alternative thinking for tunable thermal management based on the dynamic utilization of the hot sun and cold universe.

The feasibility of integrating the radiative sky cooling ability of common photovoltaic cells into the photovoltaic-thermoelectric cooler to further enhance the space cooling energy density is analyzed in this paper. Specifically, daytime cooling is obtained by the photovoltaic panel powering the thermoelectric cooler while the same photovoltaic panel provides nighttime radiative sky cooling. To achieve an optimal temporal match between the new method’s output cooling power to a cooling building’s time-varying cooling load (with 4 occupants and 24 m2 floor space), two thermoelectric cooler modes of operation are studied; The first continuously operates the thermoelectric cooler power at the time-averaged value while the second directly supplies the photovoltaic power to the thermoelectric cooler in the daytime. Furthermore, a spectral model is used to accurately estimate the radiative energy of crystalline solar cells based on their emissivity spectrum. It is found that radiative sky cooling can almost double the equivalent solar to cooling coefficient of performance over the basic photovoltaic and thermoelectric cooler system (from 0.1099 to 0.2054). The photovoltaic area only needed to be 12–17 m2, and the second operating mode can better match the supply versus cooling demand ratio while yielding a relatively consistent 10 °C difference throughout the entire day.

The thermoelectric generator (TEG) is a clean and noiseless renewable electrical power source that requires no moving parts. In the meantime, the hybrid photovoltaic cell and thermoelectric generator (PV/TEG) system is also popularly considered in research because of its potential improved power conversion efficiency over its monolithic counterparts. This paper continues the work on several previous publications from the authors where the focus here is to perform maximum power point tracking (MPPT) on the hybrid PV/TEG system. It reuses the Lock-On Mechanism (LOM) MPPT algorithm which was previously used by the authors in two separate publications on the solar panel and TEG alone. In comparison to conventional fixed step based MPPT algorithms, the LOM algorithm improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle whenever the MPP is located. In doing so, the steady state oscillations become negligibly small thus be considered eliminated and a smooth steady state MPP response is achieved. The simulation and experiment in this paper are conducted using a double SEPIC converter where each input source is treated independently with the proposed algorithm. Results prove that the proposed algorithm is fast and stable in comparison to the conventional fixed step hill climbing algorithm.

The thermoelectric generator (TEG) is a clean and noiseless renewable electrical power source that requires no moving parts. Unfortunately, the practicality of TEGs is currently limited by its typical low conversion efficiencies. Subsequently, researchers have taken many approaches to improve the efficiency of the TEG. One of such approaches is the utilization of maximum power point tracking (MPPT) techniques. MPPT techniques are popularly used in literature for maximizing the power that is extracted from solar panels. Such techniques can be reused for the TEG scenario because TEGs also have I-V and P-V characteristics that follow the same principles as that of solar panels. This paper presents a “Lock-On Mechanism” MPPT algorithm and applies it specifically to the TEG application. In comparison to conventional fixed step based MPPT algorithms, the proposed algorithm improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle whenever the MPP is located. In doing so, the steady state oscillations become negligibly small thus be consideredeliminated and a smooth steady state MPP response is achieved. Simulation and experimental results prove that the proposed algorithm is fast and stable in comparison to the conventional fixed step hill climbing algorithm.

Maximum power point tracking (MPPT) techniques are popularly used for maximizing the output of solar panels by continuously tracking the maximum power point (MPP) of their P-V curves, which depend both on the panel temperature and the input insolation. Various MPPT algorithms have been studied in literature, including perturb and observe (P&O), hill climbing, incremental conductance, fuzzy logic control and neural networks. This paper presents an algorithm which improves the MPP tracking performance by adaptively scaling the DC-DC converter duty cycle. The principle of the proposed algorithm is to detect the oscillation by checking the sign (ie. direction) of the duty cycle perturbation between the current and previous time steps. If there is a difference in the signs then it is clear an oscillation is present and the DC-DC converter duty cycle perturbation is subsequently scaled down by a constant factor. By repeating this process, the steady state oscillations become negligibly small which subsequently allows for a smooth steady state MPP response. To verify the proposed MPPT algorithm, a simulation involving irradiances levels that are typically encountered in outer space is conducted. Simulation and experimental results prove that the proposed algorithm is fast and stable in comparison to not only the conventional fixed step counterparts, but also to previous variable step size algorithms.

In this paper, the seepage finite element method (FEM) is used to simulate the transient seepage of Beijiang Dike, and antiseepage solutions are designed and discussed. By comparing the measured data of a piezometer with the steady-state calculation model, the calculated results are compatible very well with the measured data. Aiming to improve the ability to respond in extreme weather conditions, we calculate the transient seepage field after the water level suddenly rises in a short time and then select the relief well as the antiseepage measure and optimize it. The results show that when the water level is 15.78 m, the slope reaches 0.5, and the embankment is damaged. With the increase of penetration depth, the effect of drainage and decompression in the depth of 3/5 and 4/5 is relatively small due to geological strips. Due to different geological conditions, the same relief wells are placed in different positions with a wide gap in effect, the antiseepage effect is the best when the horizontal distance is 95 m, and the effect is the best when the depth is 16.5 m. The research results can be used to guide the seepage prevention and control design of Beijiang Dike.

The energy efficiency of fuel cell-based cogeneration systems is limited by the stack’s natural characteristics, and fuel cell water recovery is an energy-consuming process. Here, an alternative system concept is proposed, which recycles the fuel cell’s waste heat to the thermoelectric heater’s cold side to increase its temperature. Hence, the temperature difference across the thermoelectric cooler drops to increases the coefficient of performance for water heating. Furthermore, by cooling the fuel cell’s flue gas, by-product liquid water recovery is achieved. A system-level mathematical model is developed to combine the 1 kW fuel cell stack and thermoelectric cooler/heater model, which analyzes the hybrid system’s performance for efficiently generating power, heat, and drinking water. During the analysis, the hot side temperature, thermoelectric cooler size, and humification rate have been parametrically swept. Results show that adopting thermoelectric modules of 12 or more and lowering the airflow rate to 0.02 kg/s enabled energy efficiencies of up to 1.1 under an ambient 283.15 K and reference 323.15 K temperature heat transfer conditions. Also, up to 1.5 kg/h of liquid water could be recovered if the water-heating temperature is changed to 308.15 K.

This paper proposes to utilize the waste heat of a solar-driven Organic Rankine cycle (ORC) to support the regeneration process of the carbon capture by adsorption (CCA) subsystem. The waste heat is utilized in cascaded form, where the higher temperature component is supplied to the CCA device, and the lower temperature component is internally exchanged to increase the ORC efficiency. The proposed system is studied for the microgrid application, where a thermodynamic analysis is conducted to evaluate the electrical and exergy performance of the proposed system under 1 day of solar irradiance. The analysis is achieved by coupling the simulation models of each subsystem, where the influences of the ORC pressure ratio, turbine inlet temperature, regeneration temperature, and the CO2 input source are investigated. Results show that the proposed system is optimal when combined with CO2 capture of the animal farm; When a 50 m2 and 100 solar concentrations solar thermal plant is used, an optimal regeneration temperature of 75 °C existed to yield 4375.6 kg of CO2 per day and 0.3 MW electricity. The corresponding ORC and C O 2 capture exergy efficiencies are 0.25 and 0.012, respectively, which sum to be higher than the basic solar-ORC under the same conditions.

Although interfacial atmospheric water generation is a new concept that can generate freshwater from renewable energy, its water generation rate is too low for widespread use. This paper proposes to integrate the fuel cell to a similar device but instead uses the electrochemically generated waste heat to drive the regeneration process of the liquid sorbent material. Furthermore, the electrochemically generated water is used to increase the relative humidity of the incoming air. Thus, by solely relying on the fuel cell waste products, water recovery rates that are theoretically higher than direct atmospheric water generation are achieved. A steady-state physics model based on the difference in water partial pressure to achieve water absorption and desorption is used to analyze the liquid sorbent device’s performance. Furthermore, the effect of various design parameters such as the salt mass fraction, the fuel cell operating power, the ambient relative humidity, etc. have been studied. Results demonstrate that up to 1.8 kg/h and 0.82 kg/(m2 h) of liquid water can be obtained by fuel cells with an operating temperature range that is consistent with the high-temperature proton exchange membrane fuel cell. This implementation would allow an FC waste heat utilization ratio of up to 0.8.

Maximum power point tracking (MPPT) techniques are popularly used for maximizing the output of solar panels by continuously tracking the maximum power point of their P-V curves, which depend both on the panel temperature and the input insolation. Various MPPT algorithms have already been studied in literature, including perturb and observe (P&O), hill climbing, incremental conductance and neural networks. In particular, fuzzy logic control (FLC) is an another popular technique which achieves a significantly improved performance in MPPT in terms of response speed and no oscillations about the maximum power point (MPP). Unfortunately, a major issue that arises in classical FLC based MPPT algorithms is the lack of versatility to rapidly changing environmental conditions such as the applied irradiance. This paper presents an alternative design of an adaptive MPPT fuzzy logic controller which utilizes simple formulae instead of complex learning algorithms to adjust the antecedents. To verify the proposed MPPT system, a customized off the shelf solar panel is connected to a SEPIC converter and the overall system is both simulated on Simulink and experimentally verified. The resulting response is shown to be fast and stable in comparison to previous designs which used fixed fuzzy logic antecedents that need to be manually modified whenever the environmental conditions change or if a different solar panel is used.

The thermoelectric generator (TEG) has been widely considered as an electrical power source in many ground applications because of its clean and noiseless characteristics. Moreover, the hybrid photovoltaic cell and TEG (PV/TEG) system has also received wide attention due to its improved power conversion efficiency over its monolithic counterparts. This paper presents a study of the dynamics and the operation of the hybrid PV/TEG system in an outer space environment where a unified thermodynamic model of this system is presented. Moreover, the multi-objective NSGA-II genetic algorithm is utilized to optimize the design of the TEG both in terms of optimal output power and in terms of mass. Specifically, the design of the single stage and the two stage variant of the aforementioned TEG are considered. Simulation results indicate that the optimized PV/TEG system does indeed achieve better efficiencies than that of the monolithic counterparts. Furthermore, it is shown that the single stage TEG is more beneficial than the two stage TEG in terms of achieving optimal performance.

Despite the success of atmospheric water generators for providing drinking water to remote regions, this technology has a high specific energy consumption. This paper proposes to reuse the electrochemical water of the fuel cell for the vapor compression cycle based atmospheric water generator (VCC-AWG); After passing through an ambient heat exchanger to remove the electrochemical waste heat, the fuel cell flue gas that enters the VCC-AWG is at a higher relative humidity than natural atmospheric air, thus the freshwater yield per energy input can be significantly increased. Hence, the FC-VCC-AWG hybrid system is proposed to be a power and freshwater supply of a grid-independent home. The fuel cell model, the vapor compression cycle’s thermodynamic model, and humid air physics are coupled to analyze the overall system in terms of the fuel cell’s working condition, incoming airflow rate, compressor power consumption, and the ambient relative humidity. When RH = 0.75, adding a 2 kW fuel cell generated up to 3 kg/hr of freshwater, which is 50% higher than excluding the FC. The specific energy consumption can be 200 Wh/kg, so the VCC-AWG can be integrated with small sacrifices to the FC power output.

This paper presents a three-dimensional finite element analysis that couples the high temperature proton exchange membrane fuel cell (HT-PEMFC) and thermoelectric generator into a single model. The proposed model is aimed to accurately simulate this hybrid system by implementing the laminar one-phase flow, concentrated species, ideal gas law physics, electrochemical dynamics of the HT-PEMFC, and the thermoelectric effect of the thermoelectric generator. Furthermore, the thermoelectric generator size, characterized by the number of thermocouple legs, has also been varied to additionally analyze how this parameter will influence the thermoelectric generator and HT-PEMFC’s performances under an identical 353.15 K temperature boundary condition that is representative of domestic hot water. Results show that, for a 7.5 cm by 3 cm fuel cell, increasing the thermoelectric generator size would also increase the current density, heat generated and the output power of the fuel cell. However, higher cathode water and hydrogen concentrations by around 25% and 7% respectively were also found from using a larger thermoelectric generator, which is not favorable from the lifetime perspective. Moreover, adopting a smaller thermoelectric generator size such as the one with 2 pairs of thermocouples increased the thermoelectric generator’s output efficiency to around 1.2%.