Unit Power Research Articles

Bone Quality as Measured by Hounsfield Units More Accurately Predicts Proximal Junctional Kyphosis than Vertebral Bone Quality Following Long-Segment Thoracolumbar Fusion

To compare the prognostic power of Hounsfield units (HU) and Vertebral Bone Quality (VBQ) score for predicting proximal junctional kyphosis (PJK) following long-segment thoracolumbar fusion to the upper thoracic spine (T1-T6). Vertebral bone quality around the upper instrumented vertebrae (UIV) was measured using HU on preoperative CT and VBQ on preoperative MRI. Spinopelvic parameters were also categorized according to the Scoliosis Research Society-Schwab classification. Univariable analysis to identify predictors of the occurrence of PJK and survival analyses with Kaplan-Meier method and Cox regression were performed to identify predictors of time to PJK (defined as ≥10° change in Cobb angle of UIV+2 and UIV). Sensitivity analyses showed thresholds of HU < 164 and VBQ > 2.7 to be most predictive for PJK. Seventy-six patients (mean age 66.0 ± 7.0 years; 27.6% male) were identified, of whom 15 suffered PJK. Significant predictors of PJK were high postoperative pelvic tilt (P= 0.038), high postoperative T1-pelvic angle (P= 0.041), and high postoperative PI-LL mismatch (P= 0.028). On survival analyses, bone quality, as assessed by the average HU of the UIV and UIV+1 was the only significant predictor of time to PJK (odds ratio [OR] 3.053; 95% CI 1.032-9.032; P= 0.044). VBQ measured using the UIV, UIV+1, UIV+2, and UIV-1 vertebrae approached, but did not reach significance (OR 2.913; 95% CI 0.797-10.646; P= 0.106). In larger cohorts, VBQ may prove to be a significant predictor of PJK following long-segment thoracolumbar fusion. However, Hounsfield units on CT have greater predictive power, suggesting preoperative workup for long-segment thoracolumbar fusion benefits from computed tomography versus magnetic resonance imaging alone to identify those at increased risk of PJK.

Hand-held GPU accelerated device for multiclass classification of X-ray images using CNN model

Chest X-ray (CXR) images are the primary investigation aid for many lung diseases and their follow-ups. For diagnosis of SARS-CoV-2, RT–PCR test and chest Computed Tomography (CT) are commonly used but both face false negatives for ruling out the infection. So, there is a demanding need for developing a system combined with Artificial Intelligence (AI) and CXR imaging to detect COVID-19 patients to avoid its spread. Here, a robust and efficient handheld device is proposed. It uses the computational power of the Graphics Processing Unit (GPU) and pre-trained deep learning models for analyzing the CXR images. A Resnet-50 CNN model is deployed on an NVIDIA Jetson Nano GPU module for the real-time classification of COVID-19, Tuberculosis, and Normal using CXR images. The device can perform real-time classification of CXR images from a portable X-ray machine and classify the image into one of the above categories. For the extensive training, a database of 680 COVID-19, 1230 Tuberculosis, and 1050 normal CXR images are extracted by combining several global databases like Kaggle, SIRM, RSNA, and Radiopaedia. The classification accuracy, precision, and loss rate were 0.9879, 0.9758, and 0.0196 respectively and our model would improve with larger data sets. The highly accurate and high-performance GPU device significantly plays a far-reaching role in COVID-19 diagnosis using Chest X-ray, which could be beneficial to triage the health system and to combat the outbreak of COVID-19.

Scientific and Technical Basis for the Development of an Induction Heating Unit for Milk Pasteurization

Introduction. Induction heating is a preferred heating technique for industrial, medical and consumer systems, because it has a number of advantages over traditional heat transfer methods. The advantages include energy efficiency, heating rate, safety of operation, cleanliness of the process, low metal consumption, simple design, and precise control of the temperature of the heated raw materials. An induction heating unit is especially important for farms involved in processing of milk and producing milk-based products. Aim of the Study. The study is aimed at developing a prototype unit for long-term pasteurization of milk using a container heated by induction currents and at selecting optimal operating conditions for the developed prototype unit. Materials and Methods.There was used 3D modeling in the KOMPAS-3D computeraided design system to develop the main components of a milk pasteurization prototype unit with induction heating. The container for raw materials, stirrer and lid are made of stainless steel AISI 304 and AISI 430. The inductor is a frame made of polymer material with a litz wire arranged in a spiral manner. The body of the prototype unit is made of aluminum composite material. The developing and debugging of the electronic circuit of the prototype unit power part was carried out with the use of the design program Proteus 7.10. The microcontroller Mega 2560 was used to make the power part of the electromagnetic induction generation unit. The controlled temperature was monitored by using the waterproof temperature sensor DS18B20. A thermal imager was used to visualize the propagation of the thermal field over the surface of the container walls. Results. The structure diagram of the developed prototype unit with induction heating for long-term pasteurization of milk is presented. The article gives grounds to the use of the necessary elements and actuators in the unit for pasteurization of milk in a container heated by induction currents. There are presented a diagram of the developed power part for the prototype unit and the results of testing it when heating containers made of various materials. An algorithm has been developed to control the operation and PID regulation of the milk pasteurization in an experimental unit with the use the Raspberry Pi microcomputer. The graphs of transient processes when changing the coefficients of PID temperature control are presented. Discussion and Conclusion. When testing the induction heating principle on stainless steels of different compositions, it has been concluded that for the efficiency of heating the container, there is required a ferromagnetic steel pad welded on top of the main container made of food-grade stainless steel. The developed system of inductors made it possible to create a prototype unit with two heating zones depending on the volume of processed raw materials that is important for small farms engaged in processing milk and producing milk-based products.

Studies on the Experimental Measurement of the Low-Frequency Aerodynamic Noise of Large Wind Turbines

With the continuous warming of the global climate, expanding the use of renewable energy has become one of the main social responsibilities. However, as the number of installed wind turbines and their physical dimensions continue to increase, the issue of generated noise has become increasingly significant in influencing the acceptance and endorsement of wind power projects by neighboring communities. In this paper, we investigated the noise generated by two wind turbine units with rated powers of 1.5 MW and 4.5 MW and analyzed the variations in low-frequency noise during their operation and shutdown periods. This research shows that the power of a single unit has a significant impact on the low-frequency noise emitted into the environment. Compared with 1.5 MW wind turbines, 4.5 MW wind turbines generate more low-frequency noise when operating at the same wind speed. Further analysis of the narrowband frequency spectra and one-third octave spectra of the measured noise indicates that the low-frequency noise from the 4.5 MW wind turbine increases significantly in the range of approximately 80 Hz to 300 Hz, with more pronounced variations below 250 Hz corresponding to changes in wind speed. However, the overall variations in low-frequency noise with wind speed are not as notable as those observed for the 1.5 MW wind turbine. Due to the relatively weak attenuation of low-frequency noise in the atmosphere, the higher low-frequency content of large wind turbines may cause more distress to residents near wind farms. The result of this study emphasizes that in the planning and design of wind power projects, in addition to considering the efficiency of single-unit power generation and the contribution of renewable energy, it is also necessary to pay full attention to noise emission issues to ensure that the project is widely supported and accepted in the community.

Large Signal Stability Analysis of Hybrid AC/DC Microgrids When a Single-Phase-to-Ground Fault Occurs

Islanded hybrid AC/DC microgrids lack support for a large grid, and the negative incremental impedance of constant power loads (CPLs) aggravates the poor anti-disturbance capability of the system. When a single-phase ground fault (SPGF) occurs, the amount of fault impulse power that islanded AC/DC hybrid microgrids can stably withstand and when the protection equipment can work are both unknown. In this paper, the method of symmetrical components is utilized, and high-signal stability criteria for islanded hybrid AC/DC microgrids when a SPGF occurs are derived based on the mixed potential theory. The proposed criteria place quantitative constraints on the power of the PV unit, DC/AC converter current inner-loop proportional parameters, inductors, and inductor equivalent resistance, as well as energy storage unit power, CPL power, capacitors, DC bus voltage, line equivalent resistance, line equivalent inductance, equivalent inductance in the faulty branch, equivalent resistance in the faulty branch, positive-sequence equivalent impulse power of the SPGF, and zero-sequence equivalent impulse power. Furthermore, the maximum impulse power of a SPGF that islanded hybrid AC/DC microgrids could stably withstand is also presented, providing guidelines for protection equipment to decide when to work. In addition, the allowable maximum CPL power that islanded hybrid AC/DC microgrids could steadily support as a SPGF occurs is deduced, and the power is usually adopted to determine the states of an energy storage unit and load shedding in advance. Simulation and experimental validations prove the correctness of the derived high-signal stability criteria.

Influence of coupling air conditioner with hybrid PCMs on building interior conditions and consumed power: Experimental investigation

Air conditioning systems are vital for modern comfort but consume a substantial portion of global energy, contributing to environmental concerns and rising energy costs. PCMs can store and release energy during phase transitions, making them promise to reduce cooling loads. This study endeavors to empirically investigate the influence of integrating hybrid Phase Change Materials (PCMs), specifically PCMSP24E and PCMSP26E, with a real vapor compression refrigeration system. The primary focus is on assessing the consequential effects on the energy consumption of the refrigeration system and the interior environmental conditions within a building, including temperature and relative humidity. The energy usage of the split air conditioner wherein the outdoor unit is attached to PCMs tube heat exchanger for precooling the incoming air is investigated. Experiments reveal that PCM precooling effectively reduces the ambient air temperature entering the air conditioning condenser, leading to substantial energy savings. Increasing the PCM quantity enhances the system performance and refrigeration unit power saving. With 11 kg of PCMs, energy consumption by the air conditioning system decreases by 10.4 %, and indoor air temperature and relative humidity reduce by 0.5° and 5 %, respectively. Hence, PCM integration ensures a more consistent indoor temperature profile, enhancing occupant comfort and reducing temperature fluctuations.

Federated learning-based trajectory prediction for dynamic resource allocation in moving small cell networks

With the evolution of fifth generation (5G) of mobile communication, vehicular edge computing (VEC) and moving small cell (MSC) network are gaining attention because of their capability to provide improved quality-of-service (QoS) to vehicular users. The ultimate goal of VEC-enabled MSC network is to diminish the vehicular penetration effect and path loss resulting in improved network performance for vehicular users. In this paper, we explore distributed resource block (RB) allocation for fronthaul links of MSCs with probabilistic mobility in VEC-enabled MSC network. The proposed work exploits the computational power of road side units (RSUs) deployed with VEC servers present along the road sides to allocate the resources to MSCs in a distributed manner by exchanging limited information, with the objective of maximizing the data rate achieved by MSC network. Moreover, we propose federated learning (FL)-based position prediction of MSCs to predict the trajectory of MSCs in advance for efficient prediction of resource allocation in MSC network. Simulations results are presented to compare the position prediction dependent distributed and centralized time interval dependent interference graph-based resource allocation to MSCs in terms of RB utilization and average achievable data rate of MSC network. For comparison, we further investigated centralized as well as distributed threshold time dependent interference graph-based allocation of resources to MSC network.

Lipids productivity of cyanobacterium Anabaena vaginicola in an internally illuminated photobioreactor using LED bar lights

Concerns over environmental issues exists and desire to decrease of their extent, have directed efforts toward green energy production. Growth behavior of Anabaena vaginicola was determined in a photobioreator which illuminated internally (IIPBR) using LED bar light. Excessive heat generated in the IIPBR was taken care of by applying a novel air-cooled system. Further note in experimentation was to find favorable cultivation conditions in the IIPBR for A. vaginicola growth and its lipids production capacity. The following results are expressed: 80 µmol photons m−2 s−1 as light intensity, 0.5 g/l as NaNO3, and 120 ml/min as CO2 amount being expressed in terms of aeration rate. The findings were interpreted in terms of a two-component system where the genes encoded to the relevant proteins are present in cyanobacteria and their expressiveness depends on environmental stress. By determining growth rate constant as 0.11 d−1, the productivity in terms of biomass formation was calculated as 202.6 mg L−1 d−1. While rate of lipids production by the test cyanobacterium is 15.65 mg L−1 d−1. Based on total energy used for IIPBR performance, biomass productivity per unit power input equals to 0.74 g W−1 d−1 and this is in favorable position compared with other photobioreactors.

Environmental and economic dispatching strategy for power system with the complementary combination of wind-solar-hydro-thermal-storage multiple sources

The linkage, coordination, and complementary cooperation of energy supply can improve the efficiency of transportation and utilization. At present, the level of new energy consumption needs to be improved, the coordination of the source network load storage link is insufficient, and the insufficient complementarity of various types of power sources in the power system. This article fully explores the differences and complementarities of various types of wind-solar-hydro-thermal-storage power sources, a hierarchical environmental and economic dispatch model for the power system has been established. Among them, the upper level model takes the flexible consumption of new energy as the optimization goal, the middle level model uses a combination of hydropower station and energy storage to minimizes the fluctuation variance and peak-to-valley difference of the net load curve, the lower level model aims to achieve optimal environmental and economic benefits of the power system, comprehensively considers the coal consumption cost, startup and shutdown cost, energy storage operation cost, and pollutant emissions of thermal power units, determines the startup and shutdown mode and output power of thermal power units. Finally, an improved IEEE 6-machine 30-node system is used as an example for simulation analysis, the results show that after applying the proposed hierarchical environmental and economic dispatch strategy of the power system, the fluctuation variance and the peak-to-valley difference of the net load curve have been reduced by 46.3% and 31.5%, respectively, and the environmental and economic benefits of the system is improved by 5.1% compared with the traditional economic dispatch strategy. It can meet the requirements of energy system cleaning and decarbonization while improving the operation economy, which verifies the effectiveness of the proposed environmental economic dispatch model.

The research on the effect of temperature of electro-surgical unit to surgical smoke distribution in theatre-in vitro and simulation study.

In electro-surgery, surgical smoke was hazard to surgeons and patient in theatre. In order to institute effective countermeasures, quantifying of the effect of tip temperature of electro-surgical unit to surgical smoke distribution in theatre was studied. The relation of tip temperature to power of electro-surgical unit through in vitro cutting experiment. Based on experiment data, the mathematical model was established to simulate the electro-surgery in laminar operation room. As the power of electro-surgical knife increased, the knife tip temperature increased. Total content of (CO, CO2, CH4, NH3) in waste gas and net flow rate of waste gas at outlet increased with the rising temperature of knife tip and formation rate of condensed tar droplets and non-viable particles also increased. Based on simulation, it was found that The maximum height of surgical smoke rising right above the incision of electro-surgical unit was increased with rising temperature of electro-surgical knife tip. There was a spread route of dispersed surgical smoke near the walls of theatre through natural convection. The polynomial fitting relationship was derived. As the tip temperature of knife increased from 200 to 500°C, maximum ascending height of surgical smoke right above the incision position of electro-surgical unit increased from 1.1 m to 1.45 m. When the tip temperature of electro-knife was more 400°C, the CO content in the surgeon's operating zone was more than 200 ppm, which would cause the surgeon's HbCO level increased. As the patient's tissue in the wound during operation was open, when the electro-knife of more than 400°C, the content of condensed tar droplets and in-viable particle was higher than 20 g/m3 and 12 g/m3 in the zone around patient's wound of open tissue, which should be hazard to health of patient.

Multi-agent system consistency-based cooperative scheduling strategy of regional integrated energy system

This article presents a multi-agent system (MAS)-consistency-based cooperative scheduling strategy for regional integrated energy system to address the real-time economic scheduling problem with high penetration of multiple flexible loads. First, the MAS-based hierarchical optimal operation framework is developed to perform the real-time scheduling, where the framework with distributed control is further developed into the hierarchical framework with low-dimensional adjacency matrix. Furthermore, the economic scheduling optimization models corresponding to hierarchical distributed control mode and distributed control mode are established. The optimal objective of the proposed control structure is to 1) minimize the total operation cost, 2) optimize the electrical and heat power of all dispatchable units in balancing energy supply-demand. The operational rule of following heat load for hierarchical distributed control mode and a hill-climbing search model for distributed control mode are proposed to achieve the consistency of agents, so as to realize the cooperative optimal dispatch of electricity and heat vectors. Simulation results validate the effectiveness of the proposed MAS-based strategy in optimizing the cooperative operation of electricity-heat vectors. The real-time energy generation and load demand can be accurately balanced. The proposed strategy can perform efficient real-time economic scheduling and has satisfied adaptive capability for random variations of flexible loads.

Energy Management Strategy for Diesel–Electric Hybrid Ship Considering Sailing Route Division Based on DDPG

The continuous evolution of the shipping industry has resulted in increasingly severe environmental pollution. Hybrid ships can be a promising solution. However, for certain aspects such as the complex power structure of hybrid ships and the different characteristics of energy sources, it is difficult to control the energy conversion and transmission process and to reasonably allocate the power output of each energy unit. In this study, an improved K-means++ algorithm was newly adopted to divide the ship’s route. Subsequently, an energy management strategy (EMS) based on the Deep Deterministic Policy Gradient (DDPG) algorithm for diesel–electric hybrid ships was established. Based on the current navigation environment, the EMS can allocate the output power of each energy unit, and optimize the working space of the diesel engine in real time. The simulation results show that the DDPG-based EMS can reduce fuel consumption by 2.3%, 5.5%, 18.1%, and 20.1% with respect to the results of the Deep Q Network (DQN), Q Learning, HAAR, and rule-based algorithms, respectively.

Non-linear control for enhanced solar power under partial shading and AC load variations

This paper solves the control problem to track the maximum power in grid-connected PV systems to catch up with the changes and meet the energy demand, given the irregular and arbitrary nature of the solar source. Our work addresses the following objectives: i) extracting the maximum available power under partial shading, ii) and having a unit power factor. To achieve the above objectives, we have integrated two control components. The first one is dedicated to the extraction of the maximum power point (MPPT) particle swarming algorithm (PSO) with a backstepping controller, by shaking on the DC/DC converter duty cycle to increase the robustness and stability of the system. The backstepping control of the three-phase voltage source inverter is the second part. To verify the effectiveness of the introduced system, modelling and simulation are verified in MATLAB/Simulink.

FUZZY CONTROL OF POWER CONSUMPTION OF ELECTROMECHANICAL EQUIPMENT OF THE MAIN DRAINAGE COMPLEX AT IRON ORE MINE

The paper presents a fuzzy control system for the consumption of electric power by pumps of the main drainage complex of a mine based on the Mamdani fuzzy inference algorithm. The proposed system has a structure with two inputs, such as water inflow and electricity cost, and one output, the power of pumping units. The choice of the Mamdani method for building a fuzzy system is due to the fact that all these inputs and outputs are subject to preliminary expert evaluation. All quantities are fuzzificated by smooth membership functions - Gaussian and sigmoid. The input values of the system are represented by linguistic variables, each of which includes five fuzzy sets that define the membership in the very low, low, medium, high, and very high levels of the corresponding input value. The output of the system contains ten fuzzy sets. During the fuzzification, it was assumed that in order to avoid overloading the pump motors, only one option is considered: their operation at maximum power when there is a very high level of mine water inflow during heavy rains or for other reasons. In all other cases, the operation of at least one of the pumps with the highest permissible power is excluded. A base of 25 fuzzy rules was formed. When defining the rules, it is assumed that in all cases when there is a high water inflow into the mine, all three pumps must be put into operation, regardless of the electricity cost in force in the current period of time. This set of rules is of the highest importance due to the need to prevent flooding of the mine. For other values of water inflow, the output power consumption of drainage pumping units depends on the current cost. This set of rules has a lower priority. We simulated the operation of the dewatering pumping system with and without a fuzzy power consumption control system. The test signal for the "water inflow" input was represented as a random variable with a normal distribution. The test signal for the "electricity cost" input was formed on the basis of real data on the price determined by the operator for the day ahead market for 12/24/2023. It was found that the use of a fuzzy system can reduce the cost of purchasing electricity by 1.24% per day. It should also be noted that the economic effect is achieved not by reducing the level of power consumption, but by rationalizing the operation of the drainage complex, which ensures maximum groundwater drainage performance when the cost of electricity is high, and minimum when it is low.

A Novel Numerical Simulation Study of Air Leakage in Rotary Air Preheaters Based on Rotor Thermal Deformation

Thermal deformation of the rotor is a critical factor leading to radial air leakage in rotary air preheaters. However, previous studies have not comprehensively established the correlation between rotor thermal deformation during thermal operation and radial air leakage. This study addresses this gap by introducing a novel model for calculating radial air leakage, incorporating the thermal deformation of the rotor. To achieve this, we selected a three-section rotary air preheater from a 330 MW coal-fired unit boiler for investigation. This research begins by constructing a heat transfer–structure coupled numerical simulation model using Fluent and ANSYS Workbench. This model is employed to analyze the thermal deformation of the rotor under varying unit power generation loads. This paper meticulously examines the thermal deformation patterns of the rotor in diverse circumstances, explores their impact on air leakages, and provides a comprehensive analysis of air leakage fluctuations in different ducts. The influence of rotor thermal deformation on the local radial leak characteristics is ultimately established. The results indicate that incorporating the impact of preheater thermal deformation into the examination of preheater air leakage enhances the model’s capacity to accurately simulate values of leakage distribution at various cell clearances. This research concludes by offering recommendations for effectively managing hot end radial air leakage in preheater systems, providing valuable insights for the design and adjustment of sealing systems.

Effects of the morphed trailing-edge flap parameters on the aerodynamic performance of NREL Phase II wind turbine

This study assesses the impact of three morphed trailing-edge flap (MTEF) parameters (flap deflection angle β, flap length b, and flap span length l) on increasing power and axial thrust coefficients and their comprehensive effect on wind turbines using computational fluid dynamics (CFD) method. The detailed analysis is performed on seven morphed blades at eight different wind velocities. The obtained results show that β results in the largest unit power coefficient increase rate and unit axial thrust coefficient increase rate, while l results in the smallest ones. In addition, b results in the largest power-thrust ratio increase rate. The optimum blade is achieved for β = 3°, b/ c = 0.3, and l/ R = 0.3, which results in additional power increase of 15.24% and axial thrust increase of 9.53% at a tip speed ratio of 5.949, compared with the original wind turbine.

Prediction of Specific Fuel Consumption of a Tractor during the Tillage Process Using an Artificial Neural Network Method

In mechanized agricultural activities, fuel is particularly important for tillage operations. In this study, the impact of seven distinct parameters on fuel usage per unit of draft power was examined. The parameters are tractor power, soil texture index, plowing speed, plowing depth, width of implement, and both initial soil moisture content and soil bulk density. This study investigated the construction of an artificial neural network (ANN) model for tractor-specific fuel consumption predictions for two tillage implements: chisel and moldboard plows. The ANN model was created based on the collection of related data from previous research studies, and the validation was performed using actual field experiments in clay soil using a chisel plow. The developed ANN model (9-22-1) was confirmed by graphical assessment; additionally, the root-mean-square error (RMSE) was computed. Based on the RMSE, the results demonstrated a good agreement for specific fuel consumption per draft power between the observed and predicted values, with corresponding RMSE values of 0.08 L/kWh and 0.075 L/kWh for the training and testing datasets, respectively. The novelty of the work presented in this paper is that, for the first time, a farm machinery manager can optimize tractor fuel consumption per draft power by carefully controlling certain parameters, such as initial soil moisture content, tractor power, plowing speed, implement width, and depth of plowing. The results show that the input parameters make a significant contribution to the output over the used data with different percentages. Accordingly, the contribution analysis showed that the implement width had a high impact on tractor-specific fuel consumption for both plows at 30.13%; additionally, the chisel and moldboard plows contributed 4.19% and 4.25% in predicting tractor fuel consumption per draft power. This study concluded that practical useful advice for agricultural production can be achieved through optimizing fuel consumption rate by selecting the proper levels of affecting parameters to reduce fuel costs. Moreover, an ANN model could be used to develop future tractor fuel-planning schemes for tillage operations.

Facile Conversion and Optimization of Structured Illumination Image Reconstruction Code into the GPU Environment.

Superresolution, structured illumination microscopy (SIM) is an ideal modality for imaging live cells due to its relatively high speed and low photon-induced damage to the cells. The rate-limiting step in observing a superresolution image in SIM is often the reconstruction speed of the algorithm used to form a single image from as many as nine raw images. Reconstruction algorithms impose a significant computing burden due to an intricate workflow and a large number of often complex calculations to produce the final image. Further adding to the computing burden is that the code, even within the MATLAB environment, can be inefficiently written by microscopists who are noncomputer science researchers. In addition, they do not take into consideration the processing power of the graphics processing unit (GPU) of the computer. To address these issues, we present simple but efficient approaches to first revise MATLAB code, followed by conversion to GPU-optimized code. When combined with cost-effective, high-performance GPU-enabled computers, a 4- to 500-fold improvement in algorithm execution speed is observed as shown for the image denoising Hessian-SIM algorithm. Importantly, the improved algorithm produces images identical in quality to the original.

Risk-aware day-ahead planning of an energy hub integrated with the carbon capture unit considering cap and trade concept, energy and carbon markets and demand side flexibility

This paper optimizes the stochastic day-ahead planning of an energy hub considering the carbon capture system, energy and carbon markets and flexible loads to achieve a sustainable economical-environmental operation. In the p÷resented model, the cap and trade concept as a successful policy in the regulatory programs of governments is considered to limit the level of environmental pollution caused by industries. In addition, various uncertainties including the power of wind and solar units, load demand and market prices are handled using scenario generation and reduction approaches. The downside risk method is also utilized to evaluate both risk-neutral and risk-averse attitudes of the decision-maker. In the following, the influence of demand side flexibility is analyzed by a time-of-use strategy for all types of loads. The results show that a risk-averse attitude with the maximum possible robustness increases the expected cost by about 19.55 %, while the expected risk reduces by about 100 %. The responsive loads notably can mitigate the impact of uncertainties, where their 10 % flexibility decreases the expected cost by about 19.02 %. The simulations validate the positive effect of carbon capture technology and the cap and trade concept on the environment; however, more strict rules and severe penalties are required.

Multi-Device Parallel MRI Reconstruction: Efficient Partitioning for Undersampled 5D Cardiac CINE.

Cardiac CINE, a form of dynamic cardiac MRI, is indispensable in the diagnosis and treatment of heart conditions, offering detailed visualization essential for the early detection of cardiac diseases. As the demand for higher-resolution images increases, so does the volume of data requiring processing, presenting significant computational challenges that can impede the efficiency of diagnostic imaging. Our research presents an approach that takes advantage of the computational power of multiple Graphics Processing Units (GPUs) to address these challenges. GPUs are devices capable of performing large volumes of computations in a short period, and have significantly improved the cardiac MRI reconstruction process, allowing images to be produced faster. The innovation of our work resides in utilizing a multi-device system capable of processing the substantial data volumes demanded by high-resolution, five-dimensional cardiac MRI. This system surpasses the memory capacity limitations of single GPUs by partitioning large datasets into smaller, manageable segments for parallel processing, thereby preserving image integrity and accelerating reconstruction times. Utilizing OpenCL technology, our system offers adaptability and cross-platform functionality, ensuring wider applicability. The proposed multi-device approach offers an advancement in medical imaging, accelerating the reconstruction process and facilitating faster and more effective cardiac health assessment.