Step Change Research Articles

Primary side control technique for capacitive power transfer system without any wireless feedback

The output voltage of capacitive power transfer (CPT) system will change if the load resistance is varied. This paper presents a method to regulate the output voltage using a controller that is located on the primary side, known as the primary side control technique. It does not require any additional components and wireless feedback, which lowers the cost and complexity of CPT system compared to the conventional control technique. Instead of directly measuring the output voltage on secondary side, it is estimated through the measured capacitor voltage on primary side. Modified sine wave control of the full-bridge inverter is adopted to regulate the output voltage. The proposed control technique is validated by the simulation via PSIM software using the practical parameters of capacitive coupler presented in the literature. Simulation results of the output voltage control against the step change in desired output voltage and load resistance indicate the performance of proposed control technique.

Control system optimisation of biodiesel-based gas turbine for ship propulsion

<p>Reducing a gas emission of shipping transportations become a main goal of international maritime organization to achieve a clean energy. One of best scenarios to achieve this goal is to shift a fossil fuel to a renewable energy-based fuel of a ship propulsion. This paper studies an optimization of a control system of the renewable-based small gas turbine engine for the ship propulsion. Proposed control system consists of a proportional-integral with engine performance limiters to avoid an engine damage. Proportional-integral gains are tuned by a whale optimization algorithm. A gain scheduling analysis of a step response is performed to obtain a searching area of tuning parameters and values of constant gains. In this step, the gains are modeled as function of plant variables. After the searching area is obtained, the proportional-integral gains are optimized using the whale optimization algorithm while the additional gains are set as constant values. Using this scenario, stable and optimal gains have been successfully achieved. Results show that the proposed method has better performance than that of the previous methods, i.e. gain scheduling and gain scheduling optimized by the whale optimization algorithm. The proposed method has lowest fitness value and does not have an overshoot problem.</p>

Low carbon optimization dispatching of energy intensive industrial park based on adaptive stepped demand response incentive mechanism

In order to reduce the operation cost and carbon emissions of the energy intensive industrial park (EIIP) system, a low-carbon optimal dispatching method considering the parameter adaptive demand response (DR) incentive mechanism is proposed. Firstly, the carbon capture system (CCS) and power to gas (P2G) equipment are introduced into the EIIP. Meanwhile, according to the different regulation types of loads’ DR capacity, a stepped DR incentive mechanism model including three parameters of interval length, compensation base price and price growth rate is proposed; Secondly, a bi-layer optimization model with the objective of minimizing the operation cost at the energy supply side and maximizing the energy efficiency at the load side of the EIIP is established. The DR Mechanism parameter optimization layer is constructed outside the two-layer optimization model, so as to establish a three-layer optimization model of the stepped DR mechanism considering parameter adaptation; The Kepler optimization algorithm (KOA) is used to optimize and implement the adaptive changes of mechanism parameters, further demonstrate the mechanism in the low-carbon optimal dispatching of EIIP; Finally, the simulation results based on multiple scenarios show that the proposed method improves the effectiveness of EIIP system operation economy and reduces carbon emissions.

Oral administration of liposome-encapsulated thymol could alleviate the inflammatory parameters in serum and hippocampus in a rat model of Alzheimer's disease

BackgroundNeuroinflammation is closely related to Alzheimer's Disease (AD) pathology, hence supplements with anti-inflammatory property could help attenuate the progression of AD. This study was conducted to evaluate the potential anti-inflammatory effects of liposome encapsulated thymol (LET), administered orally, in prevention of Alzheimer in a rat model by anti-inflammatory mechanisms. MethodsThe rats were grouped into six groups (n = 10 animals per group), including Control healthy (Con), Alzheimer's disease (AD) model, AD model treated with free thymol in 40 and 80 mg/kg body weight (TH40 and TH80), AD model treated with LET in 40 and 80 mg/kg of body weight (LET40 and LET80). The behavioral response of step through latency (Passive Avoidance Test), concentrations of interleukin-1β (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) and cyclooxygenase-2 (COX-2) and brain-derived neurotrophic factor (BDNF) were assessed in serum and hippocampus. ResultsThe results showed that significant increase in concentrations of IL-1β (P = 0.001), IL-6 (P = 0.001), TNF-α (P = 0.001) and COX-2 (P = 0.001) in AD group compared with healthy control rats. AD induction significantly reduced step through latency and revealed deficits in passive avoidance performance. The results also showed the treatment with free thymol especially in higher concentrations and also LTE could decrease serum concentrations of IL-1β (P < 0.05), IL-6 (P < 0.05), TNF-α (P < 0.05), and COX-2 (P < 0.05) and increase BDNF (P < 0.05) compared with control Alzheimer rats in hippocampus and serum. There were also significant correlations between serum and hippocampus concentrations of IL-1β (r2 = 0.369, P = 0.001), IL-6 (r2 = 0.386, P = 0.001), TNF-α (r2 = 0.412, P = 0.001), and COX-2 (r2 = 0.357, P = 0.001). It means a closed and positive relation between serum and hippocampus concentrations of IL-1β, IL-6, TNF-α, and COX-2. ConclusionsLET demonstrates its ability to attenuate neuroinflammatory reaction in AD model through suppression of IL-1β, IL-6, and TNF-α and COX-2 indicators. Hence, it can ameliorate AD pathogenesis by declining inflammatory reaction.

Nonstationary Changes in Annual Rainfall over Indonesia’s Maritime Continent

The investigation into changing rainfall patterns in the Indonesian Maritime Continent (IMC) involved testing for trends, step changes, and variance nonstationarity using the Mann–Kendall, Pettitt, and White tests, respectively. The analysis covered data from 106 meteorological stations over the period from 1981 to 2021, with all tests conducted at annual time scales to understand the evolving precipitation dynamics in the region. According to the findings of this study, the average annual rainfall in IMC is nonstationary. Rainfall has increased dramatically by 12.72 mm with a significant shift point in 1994. However, this characteristic is likely to vary if the analysis period is extended, reduced, or conducted in different time frames. The spatial analysis indicates that 35.8% of meteorological stations observed a notable increase in rainfall, while 28.3% experienced a significant shift, and 16% displayed considerable variation. Consequently, the study only partially identified the nonstationary nature of rainfall in the IMC. Moreover, the research highlights a substantial rise in rainfall in the central to eastern IMC region, whereas the central to western region predominantly shows a decrease. This nonstationary test helps avoid errors in climatic conditions and analytical methods, presenting recommendations for hydrological projects. Consequently, employing this nonstationary test helps prevent inaccuracies in understanding climatic conditions and analytical techniques, thereby offering valuable suggestions for hydrological projects.

Direct reconstruction of tissue temperature fields during thermal therapy by dynamic response matching and steady-state correction

In the field of oncology thermotherapy technology, online and real-time reconstruction of biological tissue temperature field is a fundamental work with important practical needs. In this paper, we proposed a new method for direct reconstruction of biological tissue temperature field by dynamic response feature matching and steady-state correction. Based on the bioheat transfer equation, the step response model of tissue temperature field during thermal therapy is established, and the dynamic response eigenvectors of biological tissue temperature and the steady-state gain of temperature response are determined offline. According to the optimal matching principle between the temperature dynamic response of the observation point and the internal space point of tissue, the optimal matching matrix of the dynamic response features between the observation point temperature and the internal temperature field of tissue is determined with the use of the dynamic response eigenvectors. Further, through the weighted synthesis of observation point temperature response by using the optimal matching matrix of dynamic response features, the tissue transient temperature field pre-estimation model is established. Finally, by correcting the tissue temperature field pre-estimation model with steady-state gain correction factor, the direct reconstruction scheme of temperature field based on dynamic response feature matching and steady-state gain correction is established. In this work, the non-destructive reconstruction of the internal temperature field of biological tissues during laser-induced thermal therapy is achieved based on the above direct reconstruction scheme. Numerical simulation experiments are performed to investigated the effects of pre-estimation time domain, the number of measurement points, laser irradiation form and measurement error on the temperature field reconstruction results.

Design of adaptive hybrid MPPT controllers with universal input voltage DC–DC converter for RES’s

At present, conventional energy production is absent because of the more hazardous gases released into the environment, the high effect on human health, more cost required for maintenance, plus less usefulness for highly populated areas. So, the Renewable Energy Sources are more focused for the present automotive industry application. In this work, the Proton Exchange Membrane Fuel Stack is considered for analyzing the proposed DC–DC converter circuit. The advantages of this fuel stack are high energy density, fast functioning nature, more robustness, and more usefulness for the various water membrane conditions of the fuel stack. However, the disadvantages of the fuel stack are excessive current generation, plus more current conduction losses. So, the wide voltage supply single switch power converter is introduced in this work for optimizing the current production of the fuel stack network. The merits of this converter circuit are high stability, good reliability, low voltage appearing across the switches, plus a uniform power supply. Here, the converter switching pulses are obtained by proposing the Modified Continuous Step Change Adaptive Fuzzy Logic with Grey Wolf Optimization hybrid controller. This controller provides high maximum power extraction efficiency from the fuel stack which is equal to 99.421%. Also, this controller's Maximum Power Point Tracking time is 0.0285 s.

Association of Remote Patient-Reported Outcomes and Step Counts With Hospitalization or Death Among Patients With Advanced Cancer Undergoing Chemotherapy: Secondary Analysis of the PROStep Randomized Trial.

Patients with advanced cancer undergoing chemotherapy experience significant symptoms and declines in functional status, which are associated with poor outcomes. Remote monitoring of patient-reported outcomes (PROs; symptoms) and step counts (functional status) may proactively identify patients at risk of hospitalization or death. The aim of this study is to evaluate the association of (1) longitudinal PROs with step counts and (2) PROs and step counts with hospitalization or death. The PROStep randomized trial enrolled 108 patients with advanced gastrointestinal or lung cancers undergoing cytotoxic chemotherapy at a large academic cancer center. Patients were randomized to weekly text-based monitoring of 8 PROs plus continuous step count monitoring via Fitbit (Google) versus usual care. This preplanned secondary analysis included 57 of 75 patients randomized to the intervention who had PRO and step count data. We analyzed the associations between PROs and mean daily step counts and the associations of PROs and step counts with the composite outcome of hospitalization or death using bootstrapped generalized linear models to account for longitudinal data. Among 57 patients, the mean age was 57 (SD 10.9) years, 24 (42%) were female, 43 (75%) had advanced gastrointestinal cancer, 14 (25%) had advanced lung cancer, and 25 (44%) were hospitalized or died during follow-up. A 1-point weekly increase (on a 32-point scale) in aggregate PRO score was associated with 247 fewer mean daily steps (95% CI -277 to -213; P<.001). PROs most strongly associated with step count decline were patient-reported activity (daily step change -892), nausea score (-677), and constipation score (524). A 1-point weekly increase in aggregate PRO score was associated with 20% greater odds of hospitalization or death (adjusted odds ratio [aOR] 1.2, 95% CI 1.1-1.4; P=.01). PROs most strongly associated with hospitalization or death were pain (aOR 3.2, 95% CI 1.6-6.5; P<.001), decreased activity (aOR 3.2, 95% CI 1.4-7.1; P=.01), dyspnea (aOR 2.6, 95% CI 1.2-5.5; P=.02), and sadness (aOR 2.1, 95% CI 1.1-4.3; P=.03). A decrease in 1000 steps was associated with 16% greater odds of hospitalization or death (aOR 1.2, 95% CI 1.0-1.3; P=.03). Compared with baseline, mean daily step count decreased 7% (n=274 steps), 9% (n=351 steps), and 16% (n=667 steps) in the 3, 2, and 1 weeks before hospitalization or death, respectively. In this secondary analysis of a randomized trial among patients with advanced cancer, higher symptom burden and decreased step count were independently associated with and predictably worsened close to hospitalization or death. Future interventions should leverage longitudinal PRO and step count data to target interventions toward patients at risk for poor outcomes. ClinicalTrials.gov NCT04616768; https://clinicaltrials.gov/study/NCT04616768. RR2-10.1136/bmjopen-2021-054675.

Temperature control research for laser-induction hybrid strengthening process

ABSTRACT A comprehensive control methodology has been developed to address challenges such as temperature fluctuations, inconsistent depth penetration, and compositional integrity variations during laser-induction hybrid strengthening performed with consistent power parameters. This approach synergistically integrates a fuzzy controller and a decoupling compensator. In the initial part of this study, a temperature field model was utilized to investigate the effects of different process factors on temperature profiles. The analysis of step response data facilitated the development of mathematical models that delineate the correlation between the input factors and output responses. Subsequently, a decoupling compensation technique was used to reduce the coupling effects between temperature and its rate of change. A fuzzy controller was then developed to reduce the system's reliance on mathematical models, hence improving the accuracy of the control strategy. The results indicate that the application of fuzzy PI control and the implementation of decoupling compensation, the control strategy successfully improves the performance of the controller by minimizing parameter interactions. This strategy also incorporates real-time adjustment of PI parameters. Compared to conventional PI control, this method offers improved response speed and reduced overshoot. The laser-induction hybrid strengthening technique ensures superior temperature control, maintaining steady-state temperature precision within a 1% tolerance.

Tobacco control policies and respiratory conditions among children presenting in primary care

Tobacco control policies can protect child health. We hypothesised that the parallel introduction in 2008 of smoke-free restaurants and bars in the Netherlands, a tobacco tax increase and mass media campaign, would be associated with decreases in childhood wheezing/asthma, respiratory tract infections (RTIs), and otitis media with effusion (OME) presenting in primary care. We conducted an interrupted time series study using electronic medical records from the Dutch Integrated Primary Care Information database (2000–2016). We estimated step and slope changes in the incidence of each outcome with negative binomial regression analyses, adjusting for underlying time-trends, seasonality, age, sex, electronic medical record system, urbanisation, and social deprivation. Analysing 1,295,124 person-years among children aged 0–12 years, we found positive step changes immediately after the policies (incidence rate ratio (IRR): 1.07, 95% CI: 1.01–1.14 for wheezing/asthma; IRR: 1.16, 95% CI: 1.13–1.19 for RTIs; and IRR: 1.24, 95% CI: 1.14–1.36 for OME). These were followed by slope decreases for wheezing/asthma (IRR: 0.95/year, 95% CI: 0.93–0.97) and RTIs (IRR: 0.97/year, 95% CI: 0.96–0.98), but a slope increase in OME (IRR: 1.05/year, 95% CI: 1.01–1.09). We found no clear evidence of benefit of changes in tobacco control policies in the Netherlands for the outcomes of interest. Our findings need to be interpreted with caution due to substantial uncertainty in the pre-legislation outcome trends.

Comparing hybrid method simulations to hydrogen dispersion and explosion tests

With an increase in the production and storage of hydrogen, it is likely that an increased number of explosions in which hydrogen plays a central role will occur unless a step change increase in safety is seen. Modelling releases of hydrogen and explosions arising from the delayed ignition of premixed gas clouds of hydrogen is carried out today using analytical and numerical approaches and most recently, using a hybrid methodology with the commercially available software exploCFD. Hybrid simulation methodology relies on the calculation of an analytically derived source term which is then used as an input for a 2D numerical simulation. In this paper we further our earlier validation work and test the ability of the hybrid methodology to predict flammable gas dispersion and subsequent explosions arising from hydrogen releases. Hydrogen has some particularly unique properties; it is the lightest of fuels – meaning masses involved are very small, and it has the highest laminar burning velocity – an order of magnitude greater than most hydrocarbons. The hybrid methodology is compared against previously documented 3D corner tests and dispersion tests. Excellent agreement between overpressure prediction and the reported experimental data for explosion against equivalence ratio is observed. The data from the hydrogen jet release simulations also compare extremely well to the previously reported experimental data. The results show that it is difficult to justify the use of far more laborious, time and cost-intensive purely numerical methods, or the use of largely uncertain more crude methods still widely used today.

Digital Twins in Agriculture: Orchestration and Applications.

Digital Twins have emerged as an outstanding opportunity for precision farming, digitally replicating in real-time the functionalities of objects and plants. A virtual replica of the crop, including key agronomic development aspects such as irrigation, optimal fertilization strategies, and pest management, can support decision-making and a step change in farm management, increasing overall sustainability and direct water, fertilizer, and pesticide savings. In this review, Digital Twin technology is critically reviewed and framed in the context of recent advances in precision agriculture and Agriculture 4.0. The review is organized for each step of agricultural lifecycle, edaphic, phytotechnologic, postharvest, and farm infrastructure, with supporting case studies demonstrating direct benefits for agriculture production and supply chain considering both benefits and limitations of such an approach. Challenges and limitations are disclosed regarding the complexity of managing such an amount of data and a multitude of (often) simultaneous operations and supports.

Clearance Nonlinear Control Method of Electro-Hydraulic Servo System Based on Hopfield Neural Network

The electro-hydraulic servo system has advantages such as high pressure, large flow, and high power, etc., which can also realize stepless regulation, so it is widely used in many engineering machineries. A linear model is sometimes only a simple approximation of an idealized model, but in an actual system, there may be nonlinear and transient variation characteristics in the systems. Coupling is reflected in the fact that the components or functional structures implemented by each system used for the design of hydraulic systems are not completely or independently related to each other, but affect each other. The nonlinear clearance between the actuator and the load reduces the control accuracy of the system and increases the impact, thus losing stable working conditions. In the paper, based on the nonlinear clearance problem of the electro-hydraulic servo system, a mathematical transfer model with clearance is established, and on this basis, a clearance compensation method based on the Hopfield neural network is proposed. In this way, clearance compensation can be realized by adjusting the parameters of neural network nodes, through simple and convenient operation. Finally, by setting different clearance values, the results of the step response and sine response curve before and after clearance compensation of the hydraulic system are compared, and the effectiveness of Hopfield neural network compensation clearance control is verified based on the comparison simulation results.

Optimization of BLDC-based electric vehicles: Vehicle dynamics modelling through dual-motor approach and designing a novel augmented TLBO algorithm for PID control

The work primarily focuses on increasing the efficiency of EV drive in electric two-wheeler by working on several aspects, such as modulating the vehicle’s design, optimizing the control strategy, and increasing the speed range using a dual-motor approach. The dynamics of electric two-wheeler have been discussed with a mathematical vehicle model and further tuning of several aspects. Besides, this paper also introduces a novel Augmented Teaching and Learning based Optimization (ATLBO) technique designed exclusively to control BLDC motors for the electric two-wheeler vehicle. Besides, the designed technique has been implemented for the widely used commercial e-bike of Hero Company. Most two-wheeler electric motors are mounted on the rear side of the wheel, which has a limited speed range. Therefore, an analysis has been performed to increase the vehicle’s speed range using a dual motor, from 45 km hr−1 to 62 km hr−1, proving to be a viable alternative to a single motor generally used in an electric bike. ATLBO technique has been designed against a conventional TLBO to optimize the proportional-integral-derivative (PID) controller for the speed control of a linear brushless DC (BLDC) motor. The proposed method has several advantages, including ease of implementation, a consistent convergence characteristic, and high computational efficiency. Furthermore, the literature has validated the merits of the presented novel control technique. The only disadvantage of using a dual motor is the initial cost, but the overall cost is moderated in the long-term usage for its augmented performance parameters. The performance parameters of the above technique are analyzed against other optimization techniques like conventional Teaching and Learning based optimization (TLBO), Particle Swarm Optimization (PSO). MATLAB/Simulink models the brushless DC motor and implements ATLBO, TLBO, and PSO algorithms. It has been found that the response obtained from ATLBO is comparatively much faster than other optimization techniques, which supports the motor for quick acceleration as well as more efficient in improving the step response characteristics such as rise time, settling time, and steady-state error in the speed control of a linear BLDC motor.

Self-Diagnostic Opportunities for Battery Systems in Electric and Hybrid Vehicles

The number of battery systems is also growing significantly along with the rise in electric and hybrid car sales. Different vehicles use different types and numbers of batteries. Furthermore, the layout and operation of the control and protection electronics units may also differ. The research aims to develop an approach that can autonomously detect and localize the weakest cells. The method was validated by testing the battery systems of three different VW e-Golf electric vehicles. A wide-range discharge test was performed to examine the condition assessment and select the appropriate state of charge (SoC) for all three vehicles. On the one hand, the analysis investigated the cell voltage deviations from the average; the tests cover deviations of 0 mV, 12 mV, 60 mV, 120 mV, and 240 mV. On the other hand, the mean value calculation was used to filter out possible erroneous values. Another important aspect was examining the relationship between the state of charges (SoC) and the deviations. Therefore, the 10% step changes were tested to see which SoC level exhibited more significant voltage deviations. Based on the results, it was observed that there are differences between the cases, and the critical range is not necessarily at the lowest SoC level. Furthermore, the load rate (current) and time of its occurrence play an important role in the search for a faulty cell. An additional advantage of this approach is that the process currently being tested on the VW e-Golf can be relatively simply transferred to other types of vehicles. It can also be a very useful addition for autonomous vehicles, as it can self-test the cells in the system at low power consumption.

Reducing false damage detections in guided ultrasonic wave monitoring systems using a denoising autoencoder

ABSTRACT Guided ultrasonic wave (GUW) monitoring systems for pipeline structures are gaining much attention in critical sectors such as the petrochemical, nuclear and energy sectors. However, the effects of environmental and operational conditions (EOCs), especially temperature, may generate substantial false damage detections. The temperature effect may interfere with different coherent noise sources and generate unwanted peaks that are falsely identified as damage. In this paper, a denoising autoencoder (DAE) is proposed to reduce the frequency of false damage detections in GUW monitoring systems. A DAE decodes high dimensional data into low-dimensional features and reconstructs the original data from these low-dimensional features. By providing signals at a reference temperature with the fewest false damage detections, this structure forces the DAE to learn the essential features hidden within complex data. A database of GUW signals is formed based on the experimental measurements using a six-metre-long stainless steel Schedule 20 pipe. Variations in temperature and damage severity are applied to develop the database to mimic a simple step change in damage growth under EOCs. The outcomes obtained from this study show that the proposed methodology can reduce false damage detections during GUW monitoring and is valuable for pipeline safety evaluations.

Direct reconstruction of the temperature field of lithium-ion battery based on mapping characteristics

Lithium-ion (Li-ion) batteries are susceptible to the working temperature so that the monitoring is essential to the battery internal temperature. The electrochemical-thermal coupling model completely reflects the battery internal behavior. However, the high complexity and multi-field coupling make it difficult to be applied to reconstruct the battery temperature field based on state observer. Based on mapping characteristics, this work proposes a temperature field direct reconstruction scheme. And the electrochemical-thermal coupling model plays a large role in this scheme. Mapping characteristic vectors of the transient temperature field are obtained from the step response model of the Li-ion battery temperature field to charge and discharge current. Furthermore, the quantitative connection of the mapping characteristic vectors between the surface points of and the internal nodes of the battery is characterized by a relevance degree matrix. And a direct reconstruction model of the internal transient temperature field is established. The internal temperature field is reconstructed directly online and in real time via exploiting the temperature measurements on battery surface. In numerical experiments, the three-dimensional temperature field of the Li-ion battery charge and discharge processes is reconstructed. The effects of charge and discharge rates, model mismatch, and measurement errors on the reconstruction results are investigated. During the charge and discharge processes, the maximum values of the transient average error of the reconstructed temperature field are about 0.4 K and 0.3 K, respectively. And the transient average error is generally below 0.8 K when the standard deviation of measurement errors is 0.5 K.

Effect of temperature step-changes and ramps on physiological and psychological responses of occupants in office buildings in summer

Thermal conditions with step changes and ramps in air temperature (Ta) are universal in buildings. However, a comprehensive understanding of the influences of these dynamic thermal factors on thermal comfort remains elusive. This study investigated the physiological and psychological responses 16 healthy college students, including thermal sensation vote (TSV), thermal pleasure (TP), positive and negative affect schedule (PANAS), skin temperature, blood pressure, wrist pulse, and electroencephalography (EEG). The experimental procedure included step-changes from an office room (26°C) to a meeting room under five different Ta (22/24/26/28/30°C) and subsequent ramping (down/up/cycles) back to 26°C. After these different warm/cool thermal experiences, TSVs (-0.2 to 0.2) were insignificantly different and TPs (0.2 to 1.6) were significantly different (P = 0.006) at neutral condition of 26°C. Specifically, TPs under neutral conditions were higher after a warmer thermal experience than after a cooler thermal experience. Under the same Ta, TSVs were significantly lower (P=0.031) by approximately 0.5, when Ta ramping down compared to ramping up and stable warm conditions. The cheek temperature showed stronger correlations with TP and PANAS scores than with other body parts. The blood pressure was weakly correlated with TSV but exhibited a strong relationship with TP. Moreover, the TP and positive emotions exhibited strong negative correlations with wrist pulses and EEG at Theta (4–8 Hz). whereas negative emotions showed almost no correlation. These findings offer insights into refining the prevailing thermal comfort models when considering dynamic thermal factors in shaping thermal perceptions.

Study of dynamic performance of PEMFC-based CCHP system in a data center based on real-time load and a novel synergistic control method with variable working conditions

In this paper, the dynamic performance of Proton Exchange Membrane Fuel Cell-based Combined Cooling Heating and Power (PEMFC-based CCHP) system combined with a data center real-time load is studied. A novel synergistic control method is proposed to achieve optimization of energy flow between system units under fluctuating load. First, the off-design working condition models of PEMFC-based CCHP system are constructed. The delay in the changes of data center temperature is considered because of the thermal inertia under dynamic conditions. Second, the dynamic performance of PEMFC-based CCHP system to step changes of data center load is analyzed. Third, to further reveal the energy flow between units, the units output under varying load conditions are compared under the constraints of power and refrigeration supply. Finally, the dynamic performance of PEMFC-based CCHP system under the traditional control method of following electric load are revealed. A novel synergistic control method for the PEMFC-based CCHP system is proposed by refining the traditional method to optimize the energy flow between units. The result presents that the average energy efficiency reaches 78.29%. Compared with the following electric load method, the energy efficiency is increased by 6.02%. The response time of synergistic control method is 27.0 ms. Improved energy efficiency and fast response have been achieved.

Determination of effective liquid-phase diffusion coefficients by tracer method in continuous packed columns

Many industrially relevant chemical processes are affected by the liquid-phase diffusion resistance in porous materials, for example in heterogeneous catalysts. Therefore, reliable experimental methods for the determination of effective diffusion coefficients in porous structures are highly desirable. In this work, a method was developed to study the internal diffusion effects in porous media by step response experiments with tracers injected to fixed beds filled with porous particles and inert material. The tracer responses were recorded at the outlet of the bed by UV–vis spectrometry. Ethanol was used as the tracer and water as the solvent. Porous aluminum oxide particles were selected as the model material. The step responses were described with a dynamic axial dispersion model, i.e. partial differential equations for the inert and catalyst sections of the bed. The partial differential equations describing the model were discretized with finite differences and the resulting ordinary differential equations were solved numerically with a solver for stiff ordinary differential equations. From the experimental data, the dispersion coefficients of the bed and the effective diffusion coefficient in the porous aluminum oxide particles were successfully determined by non-linear regression analysis. The values of the effective diffusion coefficents had a good agreement with the liquid-phase diffusion coefficients estimated from correlations. The method is applicable for any porous material.