Minimum Speed Research Articles

Assessment of climatic impact on growth and production of rice (Kharif) and wheat (Rabi) using geospatial technology over Haryana

Global climate change could have a substantial negative influence on Indian agriculture and becoming more common and intense growing as a result of food security. Indeed, the examination of weather variability on agricultural growth and production is always complex. The weather variability impact on agricultural growth and production has been evaluated by Pearson correlation analysis among various weather variables (minimum temperature, maximum temperature, relative humidity, wind speed and rainfall), vegetation indices (NDVI and LAI) and crop yield (wheat and rice) on yearly and monthly basis for the time period from the year 1991 to 2020 in the present study. Initially, the temporal behavior of weather variables and vegetation indices have been explored on the monthly and yearly time scale for the long term (1991-2020) along with crop yield over Indian state of Haryana. After that a Pearson correlation analysis have been carried out among the weather variables, vegetation indices and crop yield on monthly and yearly time scale, individually to understand the relationship of NDVI-weather and LAI- weather along with the long-term weather impact on agricultural production. A significant correlation is found between NDVI- weather and LAI- weather on monthly and yearly basis. The positive impact of the temperature, relative humidity and rainfall is found on the rice crop production, while the wind speed showed the negative impact on the rice crop production during the Kharif season in Haryana state of India during the years 1998-2018. In case of wheat crop (Rabi season), the minimum temperature, rainfall and relative humidity supports the wheat crop production, while the maximum temperature and wind speed showed the negative impact on the wheat yield in Haryana during the years 1998-2018. Overall, this study has found the annual increase in wheat crop yield approximately 0.044 tons per hectare, and rice crop yield 0.029 tons per hectare.

Indoor Air Purifiers in the Fight against Airborne Pathogens: The Advantage of Circumferential Outflow Diffusers

Airborne particles containing pathogens such as bacteria (e.g., M. tuberculosis) or virions (e.g., influenza or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) can cause infections. It has been speculated that the outflow from indoor air purifiers with a directional outlet could entrain and spread pathogen-containing aerosol particles. To date, only the case of indoor air purifiers with a directional outflow has been considered, and here we investigate an indoor air purifier with a circumferential outflow diffuser—an alternative design solution that is already commercially available. We measured the airflow velocity at two different angles to the surface of the circumferential outflow diffuser and two blower speeds. We visualized in scattered light the deflection of a vertical mist spray cone from a sneeze-simulating nebulizer parallel to the side of the air purifier. We found a significant difference in airflow velocities for different angles to the circumferential outflow diffuser: 0.01–0.02 m/s for 0° vs. 0.01–0.65 m/s for 45° at 1 m distance. We observed no significant deflection of the sneeze-simulating spray cone at the minimum blower speed and a 5 cm deflection at the maximum speed. The deflection of the sneeze-simulating spray mist particles by the tested indoor air purifier with the circumferential outflow, under the experimental conditions, is low relative to the recommended safer distances between people in indoor spaces. We conclude that indoor air purifiers with circumferential outflow diffusers have a lower potential to spread infectious aerosols in indoor spaces compared to devices with unidirectional outflow.

Energy Performance of Room Air-Conditioners and Ceiling Fans in Mixed-Mode Buildings

Studies show that people can tolerate elevated temperatures in the presence of appreciable air movement (e.g., from using ceiling fans). This minimises the use of air-conditioners and extends their set-point temperature (Tset), resulting in energy savings in space cooling. However, there is little empirical evidence on the energy savings from using ceiling fans with Room Air-Conditioners (RACs). To address this gap, we analysed the energy performance of RACs with both fixed-speed compressors and inverter technology at different set-point temperatures and ceiling fan speed settings in 15 residential Mixed-Mode Buildings (MMBs) in India. Thermal comfort conditions (as predicted by the Indian Model for Adaptive Comfort-Residential (IMAC-R)) with minimum energy consumption were maintained at a set-point temperature (Tset) of 28 and 30 ∘C and a fan speed setting of one. Compared with a Tset of 24 °C, a Tset of 28 and 30 °C resulted in energy savings of 44 and 67%, respectively. With the use of RACs, a configuration with a minimum fan speed was satisfactory for an optimal use of energy and for maintaining the conditions of thermal comfort. In addition, RACs with inverter technology used 34–68% less energy than fixed-speed compressors. With the rising use of RACs, particularly in tropical regions, the study’s outcomes offer a significant potential for reducing space-cooling energy consumption and the resultant greenhouse gas (GHG) emissions.

Hyperledger Fabric-Based Tea Supply Chain Production Data Traceable Scheme

With the advent of Industry 4.0, blockchain is one of the emerging technologies that can be used in multiple fields, especially in supply chain networks, where it is considered a sustainable concept technology. Because of its decentralization, reliability, transparency, consistency, and traceability, blockchain can challenge existing conventional models in supply chain scenarios. Therefore, this study proposes a framework that integrates the technology of Blockchain 3.0 (Hyperledger Fabric) into the tea supply chain. The concept of data traceability driven by blockchain technology consists of documenting the tea supply chain system, in which the cultivation, processing, and retailing of tea leaves are documented, and optimizing the existing anti-counterfeiting mechanisms. The ECDSA algorithm is used to confirm the identity among the entities located in the Hyperledger Fabric channel, and IPFS technology is introduced to store tea traceability data to solve the problem of data increment in the tea production process. Only the hash value and traceability code of the traceability data are stored in the block. We analyze the relationship between the number of transactions and latency, and we can see the latency time of both write and read transactions. The system tested write transactions and read transactions with a minimum write speed of 0.97 s and a maximum of 6.26 s and a minimum read speed of 0.1 s and a maximum of 4.62 s via Caliper analysis. The experimental results show that the performance analysis sounds good. This study uses distributed theory and service-oriented thinking in its specific application to the tea supply chain system model and takes each entity through a B2B connection to achieve anti-counterfeit traceability in the tea supply chain of a regulatory nature.

A high-resolution daily global dataset of statistically downscaled CMIP6 models for climate impact analyses

A large number of historical simulations and future climate projections are available from Global Climate Models, but these are typically of coarse resolution, which limits their effectiveness for assessing local scale changes in climate and attendant impacts. Here, we use a novel statistical downscaling model capable of replicating extreme events, the Bias Correction Constructed Analogues with Quantile mapping reordering (BCCAQ), to downscale daily precipitation, air-temperature, maximum and minimum temperature, wind speed, air pressure, and relative humidity from 18 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). BCCAQ is calibrated using high-resolution reference datasets and showed a good performance in removing bias from GCMs and reproducing extreme events. The globally downscaled data are available at the Centre for Environmental Data Analysis (https://doi.org/10.5285/c107618f1db34801bb88a1e927b82317) for the historical (1981–2014) and future (2015–2100) periods at 0.25° resolution and at daily time step across three Shared Socioeconomic Pathways (SSP2-4.5, SSP5-3.4-OS and SSP5-8.5). This new climate dataset will be useful for assessing future changes and variability in climate and for driving high-resolution impact assessment models.

Energy Analysis of a Novel Turbo-Compound System for Mild Hybridization of a Gasoline Engine

Efficient and low-polluting mobility is a major demand in all countries. Hybrid electric vehicles have already shown to be suitable to respond to this need, being a reliable alternative to conventional cars, at least in urban environments. Nevertheless, such vehicles present a yet unexplored potential. In this paper, we will investigate how the powertrain efficiency may possibly benefit, in an integrated drivetrain for a hybrid electric vehicle, based on a turbocharged gasoline engine, of an innovative supercharging system. The compressor and turbine will be mechanically decoupled so as to independently optimize their operation, avoiding turbo lag and maximizing energy recovery by completely eliminating the waste-gate valve. This, in turns, requires changing the turbine so as to have a flattest possible efficiency/load curve. Therefore, an ad-hoc designed turbine will be implemented in the decoupled configuration, to be used to drive an electrical generator and produce electrical energy for charging the battery. This study presents a preliminary assessment of the potential of a turbo-compounded system for a 1L turbocharged gasoline engine for a small city car. To this aim, a one-dimensional dynamic model of the engine has been built in GT-Suite and has been calibrated and validated by means of experimental data obtained on a dynamometer, both in steady state and dynamic conditions. In particular, the model has been calibrated by means of experimental data obtained in stationary conditions and its robustness has then been verified through experimental data obtained under transient conditions. The model also includes data retrieved from the characterization of the existing turbine and compressor, while a new performance map for the turbine has been designed to better exploit the potential of the components’ decoupling. Results include the estimation of energy recovery potential of such a solution. Under the implementation of a straightforward control strategy, which runs both compressor and turbine at the same speed, the system is able to achieve a 60.57% increase in energy recovered from the exhaust gasses in the turbine. Afterwards, an attempt was made to limit the minimum turbine speed to 45000 rpm and simultaneously decrease the instantaneous speed by 3000 rpm compared to the compressor, attaining a further increase of 1.7% in the energy recovered by the turbine.

Impacts of Roadside Vegetation and Lane Width on Speed Management in Rural Roads

Effective speed management in transition areas is crucial. Although numerous studies have proposed countermeasures to ensure driving safety, little research has been conducted on identifying effective and low-cost countermeasures for speed management when transitioning from rural roads to small towns. This study proposes two countermeasures: roadside vegetation and change in lane width and investigates the impact of these countermeasures on speed management performance in this context using a driving simulator experiment. Thirty participants completed eight scenarios, and countermeasures were evaluated based on stabilized speed, minimum speed, and in-town average speed. Results showed that stabilized speed and minimum speed decreased significantly in the combination of narrow lane and different vegetation designs compared to the baseline. Post-countermeasure in-town average speed didn’t decrease significantly in all scenarios. These findings suggest that roadside vegetations and narrow lane width can be effective for speed management in the transition from rural roads to small towns.

Investigation on the effect of coating properties on transient mixed lubrication of gas foil bearing

To reveal the effect of coating properties on the mixed lubrication evolution during the start–stop process of gas foil bearing (GFB), a transient gas mixed lubrication-wear model for coating surface is established. In the developed model, a method of the extended equivalent modulus by the film thickness ratio is proposed, which can extend the classic Greenwood and Tripp contact model for homogeneous materials to the coating contact involving layered materials. Moreover, a gas foil bearing start–stop experiment is conducted to verify the predicted results of the developed model. The effects of coating materials and standard deviation of coating surface on the start–stop performance of GFB are investigated. Within the scope of this article, the results show that during start-up, the gas film pressure first increases and then decreases with the increase in time, the minimum film thickness increases, while the asperity contact decreases. The opposite evolution is observed during shut-down. Compared with uncoated GFB, the friction torque and lift-off speed of GFB with polyimide (PI) and polytetrafluoroethylene (PTFE) are reduced, with PI reducing friction torque by 24.27% and PTFE by 49.03%. The minimum lift-off speed with PTFE is the smallest. The lift-off speed, friction torque, and wear volume increase with the increase in the standard deviation of coating surface. The friction torque and lift-off speed decrease as the start–stop cycle increases until both reach stability. This paper can provide theoretical guidance for the design of the top foil coating surface of GFB.

Multi objective Optimizations of friction stir welding process parameters for reinforcement of copper particles in aluminum alloy using Taguchi based grey relational analysis (GRA) and ANOVA.

In this paper, optimize process parameters of friction stir welding for reinforcement of copper particulate in between aluminum alloys. It is to boost the thermal conductivity and mechanical properties of base metals. Two dissimilar aluminum alloys with different mechanical properties .AA6061-AA6063. successfully joined. In addition, the introducing copper particles of 325 mesh size in between aluminum alloy 6061 and 6063. It is a direct application of rotating non-consumable friction stir welding tool plunged for reinforcement. Introduction of a copper particle in between aluminum alloy is a unique system in the solid-state welding process. Taguchi method as an optimization tool used to design process parameters. Afterward, welding samples were cut in the desired size and progressed for a further test such as tensile and hardness test. Finally, it is observed to have improved mechanical strength in minimum spindle speed i.e.1000 rpm and welding speed 20 mm/min. Study also shows feasibility of GRA, Hypothesis .Z-test. test and ANOVA with Taguchi technique.

Levy Flight Equilibrium Optimizer–Based Wing Design Optimization Using Functional Constraints

This paper presents wing design optimization with functional constraints using the proposed method. The proposed method is an equilibrium optimizer (EO), and it is motivated by controlling the volume mass balance method to calculate both equilibrium and dynamic states. A well-defined generation rate term is verified to strengthen the capability of the EO at exploitation and exploration. Here, the EO’s updating behavior is enhanced by Levy flight. Hence, it is named as Levy flight–based equilibrium optimizer (LFEO). The analysis device of aerodynamics is intended by combining the numerical nonlinear lifting-line method to attain the coefficients of lift and drag of the baseline wing. The proposed method is utilized for solving restricted optimization problems, and three various optimization problems are solved. The functional restrictions are connected to wing weight, wing plan form area, and root bending moment, which is included in the first optimization issue, and then the second optimization issue is created. The third optimization issue is attained by including to the second issue the state of level flight and minimum speed of the baseline unmanned air vehicle (UAV) at the maximum speed of level flight and obtainable power restrictions. It shows that describing the moment of root bending, wing area, and obtainable power restrictions at aerodynamic optimization issues may lead to various realistic wing-plane and airfoil shapes. Finally, the proposed method is implemented using MATLAB or Simulink and it is compared with existing techniques such as EO and genetic algorithm (GA).

Improvements in the Horizontal Alignment and Vertical Profile of Balampur Ghat Section in Bhopal-Vidisha State Highway Road (SH-18) using MXRoad Software

Abstract: Geometric design of highway deals with designing of physical visible features of highway those comprise of horizontal alignment, vertical profile, circular and transition curves, superelevation, Summit and valley curves, cross sectional elements, sight distances and other features. From the safety point of view, road geometric features should be well designed as per the IRC recommendation. In this research work, the horizontal alignment and vertical profile have designed of Balampur Ghat section in the Bhopal-Vidisha Road which is in the Madhya Pradesh State of India. The objective of this research work is “Improvements in the Horizontal alignment and Vertical profile of Balampur Ghat Section in Bhopal-Vidisha State Highway Road (SH-18) using MX Road Software”. The design of horizontal alignment and vertical profile have been done for Balampur ghat section approx. 2.0 km in length of State highway no. 18 (SH-18) of Madhya Pradesh. SH-18 is connected to Vidisha from Bhopal in the state of Madhya Pradesh and having heavy commercial traffic. Balampur ghat section is hilly terrain and have two improper horizontal curves along with 6.5% of vertical gradient and because of this reason that section is not safe for deriving therefore it has become an accident-prone area and the accident-prone area have the human and economical losses so it should be improved and re design of the horizontal and vertical alignment for safe design speed. The proposed methodology is on the basis of inventory survey (preliminary survey), topographic survey and MX Road software. In inventory survey take the data of existing road and find the suitable route of alternative alignment if re-alignment is required in the road. Then the topographic survey done on the existing road and alternative alignment. Import the topographic data of the road in MX Road software for generate existing surface of the road for design of horizontal alignment and vertical profile. As per IRC recommendations, there are two alternative alignments designed of the existing ghat section. As per the outputs of this research work, the length of both improved alignments is short as compare to existing road. There are no improper curves at improved alignment and maximum gradient is 4.2% which is less than the existing gradient (6.5%). The minimum design speed is 40-50 kmph which was 20 kmph in existing road. The both two improved alignments are safer as compare to existing alignment and the design speed of the vehicle has been increased. The improved alignment 2 is straighter than the improved alignment The improved alignment has also reduced the human and economic losses.

ANALYSIS OF MUD DENSITY BY USING CUTTING CAPACITY ANNULUS METHOD

Drilling mud has an important role in drilling operations, as well as lifting the cutting to the surface, controlling the pressure of the formation, and preventing the collapse of the borehole. Therefore, the drilling operations can be continued without obstacles. The function of the drilling mud depends on the conditions of the formation to be drilled for optimal results. One of the main functions is to lift cutting from a bottom hole to the surface. In the annulus, the minimum speed for lifting the cutting to the surface was calculated. The Cutting Capacity Annulus (CCA) is the value of the level of solids in the annulus. The proper concentration of cutting in the annulus is not more than 5%, to avoid drilling problems, such as decreased rate of penetration (ROP), increased drag and torque, and stuck pipe related to hole cleaning problems. In analyzing the lifting ability of cutting, CCA is very suitable to be used because it accounts for the parameters of ROP value. This study conducted a comparison of two types of natural polymers that have a function to help the hole cleaning in the drilling process. The two types of polymers are cellulose polymers (drispac) and polysaccharide polymers (starch). Furthermore, it also had been tested on a field scale using the cutting transport ratio (CTR) method to find out how much ratio is obtained in the two types of polymer mud. Based on the test of the two mud samples on the cutting removal process in the CCA method at a temperature of 150oF, the mud samples containing starch ranged from 1.0731% to 1.0792%, while the mud samples containing drispac ranged from 1.0730% to 1.0793%. At 200oF the mud samples containing starch ranged from 0.7357% to 1.3604%, while the mud samples containing drispac ranged from 0.7357% to 1.3603%. At a temperature of 250oF, the mud samples containing starch ranged from 0.2652% to 0.4903%, while the mud samples containing drispac ranged from 0.265178% to 0.4907%. Although the density of the starch-containing mud sample was greater than drispac, the CCA value did not have much effect due to the difference in density of the two mud samples of 0.1 ppg. Both samples were able to optimally lift the cutting above the surface because the CCA value was less than 5%.

ANALYSIS OF DISTRIBUTION OF NO2 POLLUTANTS IN PT. X SANGGAU REGENCY, WEST KALIMANTAN

Air pollution can come from natural activities and human activities. One type of pollutant that needs attention is air pollution caused by exhaust fumes from engine combustion and air pollution due to machines such as steam power plants. PT. X is a company engaged in the industrial sector that processes bauxite into alumina. PT. X is an example of an industry that uses coal and diesel-fired steam power plants for its factory operations. As a result of the fuel combustion process produces several exhaust gases, one of which is nitrogen dioxide, into the surrounding air. If the flue gas from the chimney exceeds the quality standard, it can pose a risk to workers and the surrounding community. Therefore, research was conducted on analyzing the distribution of NO2 pollutants from chimneys at PT. X. The data used are primary and secondary. The primary data is in the form of NO2 concentration in ambient air, while the secondary data is in wind direction and speed in one year. The known secondary data is then processed using the wrplot application so that the results are obtained in the form of the distribution of NO2 pollutants in the air. Based on the results of wind speed and direction data processing in Figure 1, it can be seen that the dominant wind direction blows from east to west with 699 occurrences, with wind speeds mostly occurring between 3.00 – 4.00 MS. Based on the wind rose above, there is no wind with a speed of less than 0.5 m/s or a calm wind. The minimum speed occurs in the range 1.00 – 2.00 m/s and the maximum speed occurs in the range ≥ 7.00 m/s.

Exploring interpretable and non-interpretable machine learning models for estimating winter wheat evapotranspiration using particle swarm optimization with limited climatic data

Accurate estimation of crop evapotranspiration (ETc) is crucial for improving the water use efficiency and designing and operating irrigation systems. To accurately calculate winter wheat ETc with limited meteorological data, the present study proposed two interpretable machine learning (ML) models (random forest (RF) and extreme gradient boosting (XGBoost)) as well as non-interpretable ML models (support vector machine (SVM) and deep neural network (DNN)) based on the particle swarm optimization (PSO) algorithm using observed winter wheat ETc data during the period from 2007 to 2013 at Luan Cheng Agro-ecosystem Experimental Station. Mean absolute error (MAE), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), and global performance indicator (GPI) were used to assess the performance of models. This demonstrated that the ML models based on the crop coefficient (Kc) and solar radiation (Rn) were accurate and offered a workaround for calculating winter wheat ETc in the absence of meteorological data. In four ML models, the ninth input combination, consisting of Kc, Rn, daily air maximum temperature (Tmax), daily air minimum temperature (Tmin), sunshine hours (n), and wind speed with a height of 2 m (U2), produced the best estimate of ETc. Among them, the PSO-based SVM (PSO-SVM) model obtained the best results for estimating ETc with MAE, RMSE, NSE, R2, and GPI values of 0.389 mm·d−1, 0.562 mm·d−1 0.910, 0.911, and 0.975, respectively, showing the advantages of the non-interpretable ML model in ETc forecasting. Accurate descriptions of actual hydrological and climatic processes were given by local interpretable model-agnostic explanations (LIME). The inflection points of daily climatic parameters (Tmin, Tmax, Rn, n) related to ETc were determined to be 3.80 °C, 5.50 °C, 1.62 MJ·m−2·d−1, 1.37 h, respectively. This work has potential to overcome the difficulty of measuring winter wheat ETc properly due to the lack of meteorological data and accomplish appropriate water management to conserve water and increase water productivity.

Analysis of travelling waves and propagating supports for a nonlinear model of flame propagation with a p-Laplacian operator and advection

In this paper, we propose a new model to characterize the behaviour of a flame driven by temperature and pressure variables. The model is formulated using a p-Laplacian operator, an advection term, and a nonlinear reaction (considering linear kinetics). First, the uniqueness and boundedness of the weak solutions are demonstrated. Subsequently, traveling wave solutions supported by the geometric perturbation theory are obtained. As a major outcome, minimum traveling wave speeds are shown to exist, for which the associated profiles of the solutions are purely monotonic with exponential behaviour. The assumptions considered in the analytical approach are further explored through a numerical assessment, and self-similar solutions are constructed to determine the evolution of the flame front in terms of the temperature and pressure variables.

A multi-criterion optimization of mechanical properties and sustainability performance in friction stir welding of 6061-T6 AA

Nowadays, the transportation industry is curious about fabricating lightweight vehicles under a sustainable manufacturing process to minimize fuel consumption costs and environmental footprints. Assessing the sustainability performance metrics of the friction stir welding (FSW) process reduces the sawing costs and environmental impacts. However, the evaluation and assessment of the sustainability performance metrics integrated with the mechanical properties of the weld joint have not been sufficiently studied. Thus, this study investigates the multi-criterion process parameter optimization of friction stir welding (FSW) to attain an optimum parameter to enhance the mechanical properties of the weld joint and decrease energy consumption and carbon dioxide emission. Experimentations are conducted using a vertical CNC milling machine on a 5 mm 6061-T6 AA material with a butt joint orientation. Tool rotational speed, traverse speed, and tool profile were used as processing parameters. Response of the study, such as transient temperature and energy consumption, was measured during the joining process, whereas hardness, tensile strength, and CO2 emission were examined post-processing. The multi-criterion optimization was done using the Taguchi-based grey relational analysis method. In addition, the transient temperature was predicted by an auto-regressive moving average (ARIMA) and Ansys simulation. The finding showed that higher rotational and minimum welding speeds had imparted a sound weld. Besides, the analysis of variance results showed that welding speed has a significant parameter at a 95% confidence interval. The proposed ARIMA model's result showed that the transient temperature prediction accuracy reached 99.922%, and the error percentage between the FEA simulation and experimental work reached 2.067%.

Study of structure evolution of ultra-rapidly annealed Fe75.3Ni10B14Cu0.7 alloys

The article concerns modern soft magnetic materials made by rapid solidification and subsequent ultra-rapid annealing. Due to the lower amount of non-magnetic elements, higher magnetisation is possible. Unfortunately, the lack of those elements causes difficulty during isothermal nanocrystallisation operation, being crucial from the final product properties point of view. Instead of isothermal heat treatment, ultra-rapid annealing (URA) is implemented. The seconds-long annealing at a higher temperature than the temperature of conventional nanocrystallisation enables material with a higher amount of ferromagnetic elements and optimal structure. It reflects in materials with good magnetic softness and higher possible magnetisation values. The amorphous alloy with Fe75.3Ni10B14Cu0.7 chemical composition in the shape of a ribbon was heat treated between cooper blocks at 773 K (500 °C) for different times in the 1–60 s range. To study structure evolution, we brought XRD, DSC, Flash DSC, Mössbauer spectroscopy, TEM, and HRTEM techniques to play. Based on the DSC results, we estimated the minimum heating speed to obtain optimal structure at 6000 K/min. The Mössbauer results allowed us to study annealing time-dependent local atomic ordering in the amorphous state. A comparison of X-Ray and synchrotron diffraction results drove us to the conclusion that X-Ray measurements are sufficient to determine the material structure. TEM shows the formation of α-Fe crystallites even after an annealing time of 0.5 s. The increase in annealing time leads to an increase in the crystalline phase volume fraction and growth of α-Fe crystallite size.

Kajian Potensi Angin Laut Sebagai Sumber Energi Terbarukan Pembangkit Listrik Pulau Kecil di Pesisir Utara Provinsi Papua

Kajian Potensi Angin Laut Sebagai Sumber Energi Terbarukan Pembangkit Listrik Pulau Kecil di Pesisir Utara Provinsi Papua

Research and Performance Optimization of Jump-Takeoff in Autogyros

The main focus of this article is on the jump-takeoff method for autogyros. On the basis of a high-confidence autogyro model, we design a jump-takeoff simulation experiment to study and optimize jump-takeoff performance. Using a simplified version of blade element theory, we conduct secondary development on the YASim dynamics library in FlightGear software and construct a highly accurate auto-rotation rotor model. The implementation of jump-takeoff requires appropriate control parameters for collective angle and pre-rotation speed. We explore the minimum collective angle condition and minimum pre-rotation speed condition to obtain the jump-takeoff envelope, and we investigate the effect of changes in control parameters within the jump envelope on jump-takeoff performance. Furthermore, we optimize the jump-takeoff performance by varying the rotor diameter and blade tip weighting. Through this study of jump-takeoff performance, we are able to determine appropriate control parameters and rotor parameters for jump-takeoff schemes, establish parameter settings for simulations of jump-takeoff tests, and thereby lay the foundation for future experimental investigations of jump-takeoff of actual autogyros.

An in vitro model to study suction events by a ventricular assist device: validation with clinical data.

Introduction: Ventricular assist devices (LVADs) are a valuable therapy for end-stage heart failure patients. However, some adverse events still persist, such as suction that can trigger thrombus formation and cardiac rhythm disorders. The aim of this study is to validate a suction module (SM) as a test bench for LVAD suction detection and speed control algorithms. Methods: The SM consists of a latex tube, mimicking the ventricular apex, connected to a LVAD. The SM was implemented into a hybrid in vitro-in silico cardiovascular simulator. Suction was induced simulating hypovolemia in a profile of a dilated cardiomyopathy and of a restrictive cardiomyopathy for pump speeds ranging between 2,500 and 3,200rpm. Clinical data collected in 38 LVAD patients were used for the validation. Clinical and simulated LVAD flow waveforms were visually compared. For a more quantitative validation, a binary classifier was used to classify simulated suction and non-suction beats. The obtained classification was then compared to that generated by the simulator to evaluate the specificity and sensitivity of the simulator. Finally, a statistical analysis was run on specific suction features (e.g., minimum impeller speed pulsatility, minimum slope of the estimated flow, and timing of the maximum slope of the estimated flow). Results: The simulator could reproduce most of the pump waveforms observed in vivo. The simulator showed a sensitivity and specificity and of 90.0% and 97.5%, respectively. Simulated suction features were in the interquartile range of clinical ones. Conclusions: The SM can be used to investigate suction in different pathophysiological conditions and to support the development of LVAD physiological controllers.