Constant Input Research Articles

PV thermal regulation and water harvesting hybrid system using evaporative cooling of silica gel layer

A proposed system for a passive cooling technique of photovoltaic (PV) via desorption cooling and water harvesting using a silica gel layer is investigated numerically. The harvested water is discussed, and the performance of the desorption-cooled PV is compared with the naturally cooled PV cell. The silica gel layer provides the water needed for evaporative cooling, so the proposed system can be used where water does not exist. The system model is presented, solved using MATLAB, and validated. The impact of the ambient conditions (ambient temperature and relative humidity), solar intensity, and silica gel layer thickness on the PV performance and silica gel uptake are presented for constant conditions and transient input weather conditions. The findings show a considerable reduction in the cell temperature and an enhancement in the cell efficiency. Also, The harvested water quantities are obtained at different operating conditions and layer thicknesses. At constant input conditions, a maximum reduction in the average PV cell temperature of 16.18 °C and an efficiency enhancement of 8.76% are achieved using a silica gel layer of 1 cm thickness. In addition, the maximum harvested water is reported as 1.238 kg/m2 for 2 cm layer thickness. For transient input weather conditions, the same performance enhancement with a reduced daily average cell temperature of 7 °C and an efficiency enhancement of 4.8% is achieved at the different silica gel layer thicknesses during 13 hr of simulation. Also, the maximum harvested water is reported as 2.35 kg/m2 for 3 cm thickness. Increasing the silica gel layer thickness influences the cell performance adversely under constant operating conditions, while this effect vanishes for actual transient input weather conditions. In contrast, increasing the thickness layer can increase the harvested water, which depends on the incident flux.

Applying parametric modelling to generate the ecosystem path of innovation and entrepreneurship education in applied undergraduate colleges and universities

Abstract This paper firstly researches the generation path of innovation and entrepreneurship education ecosystem in applied undergraduate universities from the four aspects of education ecosystem, teacher team, conceptual change and system mechanism. Then, it constructs the ecological index system of innovation and entrepreneurship education and transforms the model into a parametric model by modeling the mean value parameter and dispersion parameter and approximating the smooth function of the model by using the Bayesian P-spline method. Finally, University H is taken as an example to evaluate and test the innovation and entrepreneurship education system based on the parametric model. The results show that education and teaching occupy a large proportion of the ecosystem, indicating that by actively initiating or participating in the innovation and entrepreneurship education ecology, applied undergraduate colleges and universities can rely on social capital endeavors to prompt a constant input of resources into the ecosystem, thus maintaining the benign and sustainable development of the innovation and entrepreneurship education ecosystem.

Threshold dynamics of an uncertain SIRS epidemic model with a bilinear incidence

This paper mainly discusses the extinction and persistent dynamic behavior of infectious diseases with temporary immunity. Considering that the transmission process of infectious diseases is affected by environmental fluctuations, stochastic SIRS models have been proposed, while the outbreak of diseases is sudden and the interference terms that affect disease transmission cannot be qualified as random variables. Liu process is introduced based on uncertainty theory, which is a new branch of mathematics for describing uncertainty phenomena, to describe uncertain disturbances in epidemic transmission. This paper first extends the classic SIRS model from a deterministic framework to an uncertain framework and constructs an uncertain SIRS infectious disease model with constant input and bilinear incidence. Then, by means of Yao-Chen formula, α-path of uncertain SIRS model and the corresponding ordinary differential equations are obtained to introduce the uncertainty threshold function R 0 * as the basic reproduction number. Moreover, two equilibrium states are derived. A series of numerical examples show that the larger the value of R 0 * , the more difficult it is to control the disease. If R 0 * ≤ 1 , the infectious disease will gradually disappear, while if R 0 * > 1 , the infectious disease will develop into a local epidemic.

Experimental Implementation of Retrospective Cost Adaptive Control for Suppressing Thermoacoustic Oscillations in a Rijke Tube

Thermoacoustic systems are self-oscillating due to the fact that a constant input (e.g., fuel rate in gas-turbine combustors) yields an asymptotically oscillatory response. This behavior arises from the interaction between combustion and acoustics, resulting in thermoacoustic oscillations. Under varying operating conditions, the dynamics of thermoacoustic systems may change dramatically, which may require that active suppression controllers can be tuned for specific working conditions. This work provides an experimental investigation of retrospective cost adaptive control for suppressing thermoacoustic oscillations under sampled-data control and varying system operating conditions. This approach is first applied to a Rijke-tube emulation model for hyperparameter selection and subsequently to an experimental Rijke-tube setup. Physical experiments are conducted to investigate the performance and robustness of the adaptive controller under varying operating conditions.

Comparative performance investigations of the intervention-class underwater vehicle with different possible thruster configurations using eight identical thrusters

Different thruster configurations (TCs) or arrangements are used in underwater vehicles (UVs) to perform various deep-sea intervention operations. The location and arrangement of thrusters and the number of thrusters can vary the overall vehicle’s performance. However, a comparison study of the effect of these different TCs or performances is yet to be available in the literature. This study will provide a base for the vehicle design and choice of thruster along with their arrangements. Therefore, in this paper, computer-based numerical simulations are conducted with these TCs using eight identical thrusters on a common vehicle platform to analyze their relative performances under different operating conditions. The performance parameters studied in this paper are position error, orientation error, and energy consumed. Initially, the maximum allocated force and moments in the vehicle’s fixed frame are found by giving a constant input force to the thrusters. Then the TCs are simulated with closed-loop trajectory tracking tasks of following simple to complex profiles to identify the configurations that better perform tracking the given desired trajectories. Several computer-based simulations are conducted in the presence of underwater currents. Vectored horizontal TC (inclined to surge and sway axis) and 3D vectored TCs consume more energy than horizontal and vertical TCs. Energy consumption in horizontal and vertical TC is found to be 30 % and 23 % lesser than 3D vectored TC in the absence and presence of underwater currents, respectively, for the same trajectory tracking simulation.

On the comparison between pre- and post-surgery nasal anatomies via computational fluid dynamics

Nasal breathing difficulties (NBD) are widespread and difficult to diagnose; the failure rate of their surgical corrections is high. Computational fluid dynamics (CFD) enables diagnosis of NBD and surgery planning, by comparing a pre-operative (pre-op) situation with the outcome of virtual surgery (post-op). An equivalent comparison is involved when considering distinct anatomies in the search for the functionally normal nose. Currently, this comparison is carried out in more than one way, under the implicit assumption that results are unchanged, which reflects our limited understanding of the driver of the respiratory function. The study describes how to set up a meaningful comparison. A pre-op anatomy, derived via segmentation from a CT scan, is compared with a post-op anatomy obtained via virtual surgery. State-of-the-art numerical simulations for a steady inspiration carry out the comparison under three types of global constraints, derived from the field of turbulent flow control: a constant pressure drop (CPG) between external ambient and throat, a constant flow rate (CFR) through the airways and a constant power input (CPI) from the lungs can be enforced. A significant difference in the quantities of interest is observed depending on the type of comparison. Global quantities (flow rate, pressure drop and nasal resistance) as well as local ones are affected. The type of flow forcing affects the outcome of the comparison between pre-op and post-op anatomies. Among the three available options, we argue that CPG is the least adequate. Arguments favouring either CFR or CPI are presented.

A Hybrid Quasi-Single-Stage AC-DC Converter with Low Twice-Line-Frequency Output Voltage Ripple

Power factor correction (PFC) converters have been frequently employed in various switching power supply devices to reduce input current harmonics. However, the PFC converter suffers from an obvious twice-line-frequency output voltage ripple due to the instantaneous power imbalance between constant output power and variable input power. Suppression of twice-line-frequency ripple usually can be realized by the post-stage DC-DC converter of the two-stage cascade PFC converter; however, the two-stage cascade PFC structure is challenging to realize high efficiency since the energy is transferred twice. To achieve high power factor, high efficiency, and low twice-line-frequency ripple, a hybrid quasi-single-stage (QSS) AC-DC converter is presented in this paper, which consists of a dual output hybrid Boost/Flyback PFC converter and a Buck ripple compensation circuit (RCC). The fundamental principles of the proposed converter and the critical conditions of operation mode transition are discussed in the paper. To confirm that the twice-line-frequency ripple is effectively suppressed, the small signal model of Buck RCC is built and analyzed. Moreover, the main characteristics, including operation mode transition angle, input current, power factor, and switching frequency of the proposed hybrid QSS AC-DC converter, are analyzed. By building a 120 W experimental prototype to validate the feasibility of the proposed hybrid QSS AC-DC converter, the experimental results show that the proposed converter can realize PFC function with high efficiency and extremely low twice-line-frequency output voltage ripple.

Robust design of ARMA and ACC charts for imperfect and autocorrelated processes under uncertainty

Occurring disruptions and faults violate the perfectness of a production process in determining Economic Production Quantity (EPQ). Integrating EPQ, Statistical Process Control (SPC), and maintenance terms has brought satisfactory outcomes for such an imperfect process. Under the violated independence assumption, the Autoregressive Moving Average (ARMA) chart has been applied in the integrated models. Under autocorrelation, the extended Acceptance control chart (ACC) has indicated significant reductions in costs. Nevertheless, it has not been applied to any integrated modeling yet. Until now, constant input factors have been considered for modeling imperfect and autocorrelated processes. Uncertainty in estimating those factors can deteriorate the effectiveness of models. We present the first robust design for imperfect and autocorrelated processes under uncertainty. We apply a particle swarm optimization algorithm to provide solutions. The investigations of simple and integrated modeling indicate that applying the ACCs causes better statistical and economic results. Also, a real-life application is presented.

Feedback control of heart rate during treadmill exercise based on a two-phase response model.

This work investigated automatic control of heart rate during treadmill exercise. The aim was to theoretically derive a generic feedback design strategy that achieves a constant input sensitivity function for linear, time-invariant plant models, and to empirically test whether a compensator C2 based on a second-order model is more dynamic and has better tracking accuracy than a compensator C1 based on a first-order model. Twenty-three healthy participants were tested using first and second order compensators, C1 and C2, respectively, during 35-minute bouts of constant heart rate treadmill running. It was found that compensator C2 was significantly more accurate, i.e. it had 7% lower mean root-mean-square tracking error (1.98 vs. 2.13 beats per minute, p = 0.026), and significantly more dynamic, i.e. it had 17% higher mean average control signal power (23.4 × 10-4 m2/s2 vs. 20.0 × 10-4 m2/s2, p = 0.011), than C1. This improvement likely stems from the substantially and significantly better fidelity of second-order models, compared to first order models, in line with classical descriptions of the different phases of the cardiac response to exercise. These outcomes, achieved using a treadmill, are consistent with previous observations for the cycle ergometer exercise modality. In summary, whenever heart rate tracking accuracy is of primary importance and a more dynamic control signal is acceptable, the use of a compensator based on a second-order nominal model is recommended.

Effective Thermal Properties of a HTS Transition Edge Bolometer for High‐Flux Neutron Detection

AbstractMany applications require monitoring of increasingly high neutron flux levels. Pre‐neutron characterization is performed of a superconducting transition edge bolometric device, sensitive to neutrons by an enriched boron carbide (10B4C) layer. Heat from the absorption of neutrons is simulated using an attenuated laser, while the detector is cooled to the critical temperature, Tc. Frequency dependent (4–25 Hz) and constant input power measurements are performed on a 10B4C‐coated and a non‐coated pixel. Results are used to fit a two lumped element thermal model. The effective specific heat is highly dependent on the input pulse duration due to the interconnected stack structure. For modulated pulses, the active volume in the thermal circuit is the full depth of the substrate in the area under the pixel. For constant power input, a large portion of the substrate is heated and the interface conductivities to the cold finger are found to be important. The detectivity is D* = 3.5 × 108 , and is only slightly lower than similar detectors. Understanding the dynamics of the detector better and using neutron excitation, it is expected that optimizations can lead to an equally good detector for cold to thermal neutrons at flux levels >106 n cm−2s−1.

Modeling streamflow response under changing environment using a modified SWAT model with enhanced representation of CO2 effects

Study regionHaihe River Basin (HRB) in North China Plain. Study focusChanges in streamflow due to climate change and human activities are highly uncertain. An improved Soil and Water Assessment Tool (SWAT) model equipped with a dynamic CO2 input method was used to quantify the environmental change impacts on streamflow in the HRB. Streamflow changes were analyzed based on 22 bias-corrected CMIP6 GCMs under SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 during two 30-year periods of the middle (2041–2070) and end (2071–2100) of the 21st century relative to the historical period (1971–2000). New hydrological insights for the regionLong-term simulations of annual streamflow in the HRB demonstrated substantial discrepancies between the dynamic and constant CO2 input methods under the SSP1-2.6 and SSP5-8.5 scenarios, which highlighted the importance of using the dynamic CO2 input method for streamflow simulations. Spatio-temporal analysis using the improved SWAT model revealed that streamflow generally increased under four emission scenarios compared to the historical period. In the HRB, annual streamflow in the downstream plains was higher than in the upstream mountains, and this was more evident under the highest emission scenario of SSP5-8.5. Monthly streamflow showed considerable intra-annual variability that was generally greater from July to November. The strongest increment in streamflow was projected in the SSP3-7.0 and SSP5-8.5 scenarios, indicating that flood risk would possibly increase in the late 21st century.

Hydrogen combustion in two-stage high-pressure gas turbine—thermal and flow simulations for performance comparison with fossil fuels

Hydrogen energy forms an attractive solution for reducing greenhouse gas emissions from gas turbine systems. Although hydrogen combustion has been widely studied for combustors, only a few studies have considered the combustion effect downstream of the combustor. This study conducted an integral simulation of the combustion and flow of a GE-E3 aero-engine under hydrogen fuel and compared its performance with that of representative fossil fuels such as Jet A in an aero-engine and methane in an industrial gas turbine. All simulations were conducted under a constant heat input at the combustor and turbine inlet temperatures. During combustion simulation, the HyChem mechanism was applied to evaluate the composition of the products in an equilibrium model. Specifically, Reynolds-averaged Navier–Stokes steady simulation of a two-stage high-pressure gas turbine was conducted using the calculated boundary condition from the combustion simulation and k − ω shear stress transport γ turbulence model. The results revealed the high velocity of the hydrogen combustion flue gas owing to its low density under a large pressure difference. Overall, the power output, thermal efficiency, and fuel consumption were improved by hydrogen combustion. The thermal and flow results of the simulation can be used to develop hydrogen gas turbines.

High-efficient reversible full adder realized by dynamic threshold-based gate diffusion input logics

A new 12-transistor reversible full adder (FA) is designed based on carbon-nanotube-field effect transistors (CNTFETs) with 32 nm channel length and an area of 0.2204 μm2, 1 constant input (CI), and 3 garbage outputs (GO). The FA has 3 reversible logic gates in two of its stages that are realized by the gate diffusion input (GDI) technique. In the FA, 2 Toffoli gates with 1 CI and 1 new GDI-reversible-multiplexer are used to generate Sum and Cout, respectively. The multiplexer is 3*3, with two GOs, and a significant area reduction by only two transistors. The inputs of the circuit prevent the excessive increase of GOs and CIs. The Monte Carlo analysis using the HSPICE simulator indicates a better sensitivity of the FA versus fabrication with 6.45%, 1.86%, and 8.01% improvements of maximum values of power, delay, and power-delay-product (PDP). The FA is implemented in a 4-bit, 8-bit, 16-bit, and 32-bit ripple carry adder (RCA), and its superior results are seen. Under 32-bit RCA, the proposed circuit with 4956.30 fJ shows more energy savings compared to most competitors. The extracted results, the different figure of merits (FoMs), and reversibility features represent the proposed circuit as a desirable procedure for future works.

Anthropogenic contributions to antibiotic resistance gene pollution in household drinking water revealed by machine-learning-based source-tracking

Although the presence of antibiotic resistance genes (ARGs) in drinking water and their potential horizontal gene transfer to pathogenic microbes are known to pose a threat to human health, their pollution levels and potential anthropogenic sources are poorly understood. In this study, broad-spectrum ARG profiling combined with machine-learning-based source classification SourceTracker was performed to investigate the pollution sources of ARGs in household drinking water collected from 95 households in 47 cities of eight countries/regions. In total, 451 ARG subtypes belonging to 19 ARG types were detected with total abundance in individual samples ranging from 1.4 × 10−4 to 1.5 × 10° copies per cell. Source tracking analysis revealed that many ARGs were highly contributed by anthropogenic sources (37.1%), mainly wastewater treatment plants. The regions with the highest detected ARG contribution from wastewater (∼84.3%) used recycled water as drinking water, indicating the need for better ARG control strategies to ensure safe water quality in these regions. Among ARG types, sulfonamide, rifamycin and tetracycline resistance genes were mostly anthropogenic in origin. The contributions of anthropogenic sources to the 20 core ARGs detected in all of the studied countries/regions varied from 36.6% to 84.1%. Moreover, the anthropogenic contribution of 17 potential mobile ARGs identified in drinking water was significantly higher than other ARGs, and metagenomic assembly revealed that these mobile ARGs were carried by diverse potential pathogens. These results indicate that human activities have exacerbated the constant input and transmission of ARGs in drinking water. Our further risk classification framework revealed three ARGs (sul1, sul2 and aadA) that pose the highest risk to public health given their high prevalence, anthropogenic sources and mobility, facilitating accurate monitoring and control of anthropogenic pollution in drinking water.

The Multi-Hollow Surface Dielectric Barrier Discharge Usage for the Seeds' Treatment Aimed to the Dustiness Decrease of Free-Floating Particles from Agrochemicals

The Multi-hollow Surface Dielectric Barrier Discharge (MSDBD) generated in ambient air at atmospheric pressure was used to treat maize, pea, wheat and parsley seeds. Plasma exposure was applied as a pre-treatment before the seeds coating with agrochemicals. The aim of this study was to decrease the dustiness of coated seeds using plasma pre-treatment. The optimization process of plasma treatment parameters for individual seed species consisted of choosing a suitable exposure time (20 s, 60 s) and airflow (10 L/min, 15 L/min). The plasma made the seeds' surface more hydrophilic; therefore, better agrochemicals adhesion was achieved on the seeds' surface. Wettability improvement was demonstrated via water uptake of seeds and apparent contact angle change. Ambient air plasma at a 15 L/min flow rate was measured using optical emission spectroscopy, and the values of vibrational (3000 K) and rotational (347 K) temperatures were obtained from spectra simulation. The surface temperature of the MSDBD ceramics plate was measured with a thermal camera for different gas flow rates and constant input power of 30 W because the temperature is crucial parameter for seed treatment. The surface morphology was not affected due to plasma treatment, even for a longer exposure time. A significant decrease in dustiness measured according to the Heubach method was achieved for pea (57.1%) and parsley (41.4%) seeds. A lower decrease in dustiness was registered in the case of wheat (14.6%) and maize (17%) seeds. The results showed that MSDBD plasma generated in the air at optimized conditions is able to decrease the coated seed dustiness regardless of seed type and size, while seeds germination and surface coverage percentage remained unchanged.

Artificial Intelligence in Endoscopic Ultrasonography-Guided Fine-Needle Aspiration/Biopsy (EUS-FNA/B) for Solid Pancreatic Lesions: Opportunities and Challenges.

Solid pancreatic lesions (SPLs) encompass a variety of benign and malignant diseases and accurate diagnosis is crucial for guiding appropriate treatment decisions. Endoscopic ultrasonography-guided fine-needle aspiration/biopsy (EUS-FNA/B) serves as a front-line diagnostic tool for pancreatic mass lesions and is widely used in clinical practice. Artificial intelligence (AI) is a mathematical technique that automates the learning and recognition of data patterns. Its strong self-learning ability and unbiased nature have led to its gradual adoption in the medical field. In this paper, we describe the fundamentals of AI and provide a summary of reports on AI in EUS-FNA/B to help endoscopists understand and realize its potential in improving pathological diagnosis and guiding targeted EUS-FNA/B. However, AI models have limitations and shortages that need to be addressed before clinical use. Furthermore, as most AI studies are retrospective, large-scale prospective clinical trials are necessary to evaluate their clinical usefulness accurately. Although AI in EUS-FNA/B is still in its infancy, the constant input of clinical data and the advancements in computer technology are expected to make computer-aided diagnosis and treatment more feasible.

Experimental study on heat transfer and storage of a heating system coupled with solar flat heat pipe and phase change material unit

Using renewable energy, especially solar energy, is essential to achieve a low-carbon society. PCMs suffer from low thermal conductivity, which hinders the efficiency of phase change thermal storage systems. Heat pipes exhibit vastly superior thermal conductivity, making them a promising candidate for enhancing PCM-based systems. To solve the contradiction between building insulation and importing solar energy into buildings in winter, this study proposes a new building heating ceiling system consisting of a flat-plate heat pipe (FHP) coordinated with a phase change material (PCM), and establishes a platform for a heat stockpiling device integrating the FHP and PCM. This research investigates the impact of heating power and bending angle on the heat transfer efficiency of the heat pipe and phase change heat storage system. The experimental findings demonstrate a direct relationship between increasing heating power and the enhancement of the FHP's heat transfer efficiency. When the FHP is bent at a 5° angle and heating power is increased from 20 W to 80 W, to store heat energy into the PCM cavities, the effective thermal conductivity rises significantly, escalating from 7.26 × 104 W/(m·°C) to 15.1 × 104 W/(m·°C), marking a remarkable 108 % rise. Moreover, although increasing the bending angle leads to heightened effective thermal conductivity of the FHP under constant heat input, and the heat transfer in PCM cavities will be weakened within a bending angle of 15°, experimental results demonstrate that the melting time of PCM still decreases with the increase of bending angle; the heat transfer inertia of phase change materials is dominant.

Lake Maggiore: geomorphological genesis, lake-level evolution, and present and future ecosystems importance

Lake Maggiore, the second deeper and larger south alpine lake, was selected as a model system to detect the potential damages on water resources, biodiversity and ecosystem health caused by different water levels during the lake-level regulation period (March to November). With a drainage basin exceeding an altitude difference of 4400 m, Lake Maggiore fills a deep valley floor whose bedrock reaches up to 700 m below the present sea level. The cryptodepression occupied by the lake was probably formed during the end of the Miocene and the Pliocene and was shaped successively during the Pleistocene glaciations. Lake Maggiore originated following the Last Glaciation, when it reached its maximum lake-level and extension just after its deglaciation. The mean secular lake-level progressively decreased throughout the Holocene, causing a gradual shrinkage of the lake because of the constant depositional input that created the fluvio-deltaic plains at the mouth of the main tributaries of the lake. The regime of the tributaries is of mixed type, with a spring maximum mainly due to snowmelt and an autumn maximum exclusively of pluvial origin. Water levels naturally tend to reflect the amount of rain or snow precipitation and are expressed through a double cycle: winter and summer characterised by low waters, and spring and autumn by high waters. In 1943, the need to use the waters of the great lakes to have water available in the less favourable periods, led to the construction of a dam at the Lake Maggiore outlet. This structure allows to store water during heavy rainfall or snowmelt periods. The accumulated water is then supplied during the irrigation periods to agriculture (spring and summer) and to industrial users (mainly in autumn and winter). The geomorphological genesis and the ecosystems description was focused on riparian, fluvio-deltaic, and ephemeral systems. For these ecosystems, their evolution considering the hydrological regime of the tributaries, the anthropogenic activities in the watershed and the effects of lake-level management since 1943, was also described. Considering the summer increase, between April and July, to +1.25 m (with possible peaks to +1.50 m) experimentally tested between 2015 and 2020, and the approval of the proposal to continue the test for the next five-year period (2022-2026), we finally emphasise the potential further reduction of reeds and natural habitats and the subsequent loss of biodiversity related to the plan of raise the lake-level to +1.50 m all year round.

Automated Shape and Process Parameter Optimization for Scaling Up Geometrically Non-Similar Bioreactors

Scaling bioprocesses remains a major challenge. Since it is physically impossible to increase all process parameters equally, a suitable scale-up strategy must be selected for a successful bioprocess. One of the most widely used criteria when scaling up bioprocesses is the specific power input. However, this represents only an average value. This study aims to determine the Kolmogorov length scale distribution by means of computational fluid dynamics (CFD) and to use it as an alternative scale-up criterion for geometrically non-similar bioreactors for the first time. In order to obtain a comparable Kolmogorov length scale distribution, an automated geometry and process parameter optimization was carried out using the open-source tools OpenFOAM and DAKOTA. The Kolmogorov–Smirnov test statistic was used for optimization. A HEK293-F cell expansion (batch mode) from benchtop (Infors Minifors 2 with 4 L working volume) to pilot scale (D-DCU from Sartorius with 30 L working volume) was carried out. As a reference cultivation, the classical scale-up approach with constant specific power input (233 W m−3) was used, where a maximum viable cell density (VCDmax) of 5.02·106 cells mL−1 was achieved (VCDmax at laboratory scale 5.77·106 cells mL−1). Through the automated optimization of the stirrer geometry (three parameters), position and speed, comparable cultivation results were achieved as in the small scale with a maximum VCD of 5.60·106 cells mL−1. In addition, even on the pilot scale, cell aggregate size distribution was seen to strictly follow a geometric distribution and can be predicted with the help of CFD with the previously published correlation.

Numerical investigation of melting of a phase-change material in H-type shell tubes

This study aims to numerically investigate the melting process of a phase change material in an H-type finned concentric shell tube configuration. The H-type fins are arranged in a manner that creates an annulus structure consisting of six identical H-type fin structures. These fins are evenly spaced with equal distances between them. The phase change material used in this study is RT42, which is stored within the annulus structure to absorb heat from the inner circular tube at a constant temperature input of 70 °C. The results of the study demonstrate that the phase change material within the H-type fin tube, with a uniform width of 3 mm, exhibit significantly faster melting rates compared to narrower fin tubes. Specifically, the phase change material in the 3 mm fin tube demonstrate melting rates that are 88% and 32% higher than those observed in fin tubes with widths less than 1 mm and 2 mm, respectively.Furthermore, the study considers two additional geometric factors, namely the varying curvy angles of the first and second circular layers of the H-type fins. Melting behavior is numerically featured by varying the ratios of these curvy angles within the range of 0.68 to 1.53. Among all the H-type annulus structures of the present study, the ratio of 1.21 is the most suitable design for increasing the total energy stored, while the ratio of 1.32 is an adequate choice for improving melting performance. Additionally, the latter ratio results in a 1.68 times reduction in melting time compared to the ratio of 1. Properly arranged H-type fin structures are possibly considered a preferable design that can either enhance heat transfer or increase the total stored energy, possibly expanding PCM applicability to a more latent heat thermal energy storage systems of practical interest.