Increase In Energy Loss Research Articles

Enhanced energy storage performance in NBT-based MLCCs via cooperative optimization of polarization and grain alignment

Dielectric ceramics possess a unique competitive advantage in electronic systems due to their high-power density and excellent reliability. Na1/2Bi1/2TiO3-based ceramics, one type of extensively studied energy storage dielectric, however, often experience A-site element volatilization and Ti4+ reduction during high-temperature sintering. These issues may result in increased energy loss, reduced polarization and low dielectric breakdown electric field, ultimately making it challenging to achieve both high energy storage density and efficiency. To address these issues, we introduce a synergistic optimization strategy that combine polarization engineering and grain alignment engineering. First principles calculations and experimental analyses show that the doping of Mn2+ can suppress the reduction of Ti4+ in Na1/2Bi1/2TiO3-based ceramics and enhance ion off-centering displacements, thereby reducing energy loss and improving polarization. In addition, we prepared multilayer ceramic capacitors with grains oriented along the <111> direction using the template grain growth method. This approach effectively reduces electric-field-induced strain by 37% and markedly enhances breakdown electric field by 42% when compared with nontextured counterpart. As a result of this comprehensive strategy, <111 >-textured Na1/2Bi1/2TiO3-based multilayer ceramic capacitors achieve an ultra-high energy density of 15.7 J·cm−3 and an excellent efficiency beyond 95% at 850 kV·cm−1, exhibiting a superior overall energy storage performance.

Power Factor Optimization with Cos Phi Mode Trainee

The power factor cos phi measures the efficiency of using electrical power in a system. A low power factor indicates the presence of high reactive power consumption, which can lead to increased energy losses and operational costs. To overcome this problem, an effective power factor regulation system is required. This research designed and developed the Cos Phi Trainer, which operates in two modes, manual and automatic, to improve the power factor at an electrical load. The system is designed to give users a practical understanding of measuring and improving power factors by setting up compensation capacitors. In manual mode, the user directly sets the value of the capacitor used to fix the power factor. While in automatic mode, the system uses current and voltage sensors to measure the power factor value in real-time and automatically adjusts the capacitor to achieve the optimal power factor. The trainer has an easy-to-use interface and a measurement panel that displays important parameters such as current, voltage, active power, reactive power, and power factor. The test results show that the system can significantly increase the power factor in manual and automatic modes. Thus, this Cos Phi Trainer is an effective tool for training in the laboratory of Indorama Engineering Polytechnic and teaching about electrical power management and energy loss reduction in the electrical system. Keywords: Power factor, manual, active power, reactive power, trainer

Numerical investigation of non-uniform inflow effects on internal and external characteristics of an axial-flow pump

This paper investigates the effects of non-uniform inflow on the internal and external characteristics of an axial-flow pump. Numerical simulation is employed to study two different configurations: one with an intake sump (referred to as the intake system) and another without an intake sump (referred to as the pump system), where the intake sump introduces non-uniform inflow conditions. First, under low flow conditions, typical unstable flow phenomena are observed in the impeller, including leading edge spillage and tip leakage vortex, which are consistent with previous research findings. Second, the analysis reveals that the non-uniform inflow causes the pump system to enter the hump zone earlier, as indicated by the external characteristic curves. Energy loss analysis identifies the increased energy loss at the bell mouth due to backflow from the impeller as the main contributor to the head drop. Finally, it is observed that submerged vortices exist at the bottom of the intake sump; however, their swirling strength is insufficient to significantly affect the hump characteristics of the intake system under low flow conditions. The distinguishing factor between the two systems is the distribution of axial velocity along the radial direction in the bell mouth. The higher axial velocity near the casing of the bell mouth in the pump system supplements the energy of the liquid near the shroud side of the impeller, thus delaying the occurrence of backflow.

Insights into the optoelectronic, thermodynamic, and thermoelectric properties of novel BaYCuX3 (X = Se, Te) semiconductors from first-principles investigation

The widely used density functional theory was employed to study an intricate relationship of the optoelectronic, thermodynamic, and transport features of novel quaternary BaYCuX3 (X = Se, Te) semiconductors. The conduction band region is significantly impacted by the Ba-d and Y-d states, with negligible contributions from the S-s/p/d and Te-s/p/d states. The valence and conduction bands peak at the high symmetry Γ and Y sites, revealing an indirect energy band nature. The predicted band gaps for the BaYCuSe3 and BaYCuTe3 using the WC-GGA and TB-mBJ approximations are 0.96, 1.31 eV, and 0.54, 0.89 eV, respectively. The small atomic size of selenium in BaYCuSe3 material contributes to strong bonding, resulting in a larger energy gap as compared to BaYCuTe3. Maximum values of ε1(ω) drop as photon frequency increases, eventually approaching negative in some energy ranges. The absorption coefficient spectra shifted toward lower energy as the anion changed from Se to Te. Furthermore, the BaYCuTe3 has plasmon resonances at higher energies as compared to BaYCuSe3, resulting in increased energy loss. Furthermore, the BaYCuTe3 material exhibits maximum thermal conductivity than BaYCuSe3 across the whole temperature range.

Energy loss of a heavy fermion in a collisional QED plasma

We compute the energy loss of heavy fermions moving in a plasma, taking into account the modification of the photon collective modes induced by collisions using a Bhatnagar-Gross–Krook collisional kernel. We include contributions from both hard and soft scatterings of the heavy fermion using a collisionally modified hard-thermal-loop resummed propagator. Using this method, one does not need to introduce a separation scale between hard- and soft-momentum exchanges. To place our calculation in context, we review other theoretical approaches to computing the collisional energy loss of fermions and discuss the systematics and results obtained in each approach compared to using a resummed propagator for both hard and soft momentum exchanges. Our final results indicate that self-consistently including the effect of collisions in the self-energies of the resummed propagator results in an increased energy loss compared to using collisionless hard-thermal-loop propagators. The effect becomes larger as the magnitude of the coupling constant and the velocity of the fermion increase. Published by the American Physical Society 2024

Design of a Neural Network Model for Point-Defect Microcavities in Two-Dimensional Silicon-Based Dielectric Column Photonic Crystals

Currently, circuits are becoming more and more highly integrated, but current electronic chip technology has difficulty in meeting the requirements for increased data transmission speed and capacity because of its characteristics of increased energy loss due to interactions between electronic components. In contrast, photonic technology is a promising solution due to its characteristics of high speed, wide bandwidth, and low interaction. Photonic crystals are materials with an artificial periodic dielectric structure, with photonic bandgap and localization properties that are critical to their performance. Photonic crystals, which use photons as an information transfer medium, allow flexible control of photon propagation, just as electrons are controlled in semiconductors, and the study of multifunctional photonic crystals is important for the construction of integrated optical circuits. This paper proposes a neural network-based model to analyze and predict the optical properties of point defect microcavities in 2D silicon-based dielectric column photonic crystals. By modeling the complex relationship between the structural parameters of the photonic crystal and its optical response, a theoretical approach for the design of 2D silicon dielectric column photonic crystals can be provided.

Cavitation mitigation via curvilinear barriers in centrifugal pump

Cavitation is a significant problem in hydraulic machinery that leads to the deterioration of hydraulic performance, material damage, and flow instability. While current methods partially address cavitation instability, there is a lack of comprehensive understanding of the control mechanisms. This study focuses on controlling cavitation flow instability in a centrifugal pump by proposing an active method using obstacles on the blade's surface. A low-specific speed centrifugal pump was chosen as the research object, and a three-dimensional unsteady full-flow channel numerical simulation was conducted. The findings indicate that in the absence of cavitation, the wake vortex induced by obstacles increases energy loss in the centrifugal pump, resulting in a slight drop in efficiency. However, when cavitation occurs, the obstacles effectively improve the flow field, reduce the vortex strength near the back of the blade in the flow channel, and significantly reduce the growth rate of cavitation volume. This reduction is observed in both the cavitation volume and its first derivative. Thus, the obstacles optimize the flow structure, reduce vortex strength, and slow the growth rate of cavitation. The main control mechanism involves inducing high-pressure waves to collapse cavities and improving flow transition characteristics. To solve the inverse problem of cavitation control with obstacles inside a centrifugal pump, dimensionless geometric parameters are studied to determine better suppression effects.

Study on Oscillatory and Undulatory Motion of Robotic Fish

This paper conducts a comprehensive analysis of undulating and oscillatory movements in fish, utilizing numerical simulations to explore correlations among fin thrust and swimming speed. The study distinguishes itself through a unique approach by employing kinematic equations of motion control, specifically in oscillation and undulation, for computational fluid dynamics. Despite increasing energy loss with undulation, the study reveals a reduction in power demand with oscillation, underscoring its effectiveness in achieving desired speeds. The dynamics of undulating fins in aquatic and aerial locomotion remain insufficiently understood. The trade-off between more energy-consuming but highly propulsive movements or simpler and faster movements requires sophisticated design techniques to reduce volume. The geometry, developed using Rhino 6 software, incorporates precise fluid resistance calculations conducted with Ansys Fluent 19. Spanning flow velocities from 1 to 4 m/s were used for the simulation condition. Critical factors such as flexibility, viscosity, and shape change were meticulously examined for their impact on efficiency enhancement.

Modelling dynamical 3D electron diffraction intensities. II. The role of inelastic scattering.

The strong interaction of high-energy electrons with a crystal results in both dynamical elastic scattering and inelastic events, particularly phonon and plasmon excitation, which have relatively large cross sections. For accurate crystal structure refinement it is therefore important to uncover the impact of inelastic scattering on the Bragg beam intensities. Here a combined Bloch wave-Monte Carlo method is used to simulate phonon and plasmon scattering in crystals. The simulated thermal and plasmon diffuse scattering are consistent with experimental results. The simulations also confirm the empirical observation of a weaker unscattered beam intensity with increasing energy loss in the low-loss regime, while the Bragg-diffracted beam intensities do not change significantly. The beam intensities include the diffuse scattered background and have been normalized to adjust for the inelastic scattering cross section. It is speculated that the random azimuthal scattering angle during inelastic events transfers part of the unscattered beam intensity to the inner Bragg reflections. Inelastic scattering should not significantly influence crystal structure refinement, provided there are no artefacts from any background subtraction, since the relative intensity of the diffracted beams (which includes the diffuse scattering) remains approximately constant in the low energy loss regime.

Intelligent optimization design of large-scale three-dimensional ultrasonic vibration system

Large-scale three-dimensional ultrasonic vibration systems are susceptible to the influence of coupled vibration, resulting in a series of problems such as increased energy loss, small longitudinal displacement amplitude of the radiation surface, and uneven distribution of longitudinal displacement amplitude, which can seriously affect the working efficiency of ultrasonic processing system. How to effectively control the coupled vibration of large-scale three-dimensional ultrasonic transducer systems and optimize their performance has become an urgent problem in the field of power ultrasound. The research has found that some phononic crystal slots and point defect structures can suppress the lateral vibration of large-scale transducer systems, improve the uniformity of system amplitude distribution, and artificially regulate the performance of large-scale three-dimensional ultrasonic vibration systems by changing the configuration parameters of phononic crystal structures. However, excessive design parameters will inevitably increase the complexity of system design, and, currently, the optimization design of large-scale three-dimensional ultrasonic transducer systems relies on empirical trial and error methods which has low design efficiency and low success rate, and cannot guarantee the system performance. Therefore, in the study, homogeneous dislocations and point defect structures are introduced to optimize the design of large-scale three-dimensional ultrasonic vibration systems. Data analysis techniques are used to evaluate the influences of the configuration of homogeneous dislocations and point defect structures on the longitudinal displacement amplitude, amplitude distribution uniformity, radiated sound power, working bandwidth of the system’s radiation surface. And a predictive model for the performance of large-scale ultrasonic transducer system with homogeneous dislocation structure and near periodic defect structure is established, which can achieve intelligent design of large-scale power ultrasonic transducer system, improve design efficiency and success rate, and reduce the design cost.

An overview of critical applications of resistive random access memory.

The rapid advancement of new technologies has resulted in a surge of data, while conventional computers are nearing their computational limits. The prevalent von Neumann architecture, where processing and storage units operate independently, faces challenges such as data migration through buses, leading to decreased computing speed and increased energy loss. Ongoing research aims to enhance computing capabilities through the development of innovative chips and the adoption of new system architectures. One noteworthy advancement is Resistive Random Access Memory (RRAM), an emerging memory technology. RRAM can alter its resistance through electrical signals at both ends, retaining its state even after power-down. This technology holds promise in various areas, including logic computing, neural networks, brain-like computing, and integrated technologies combining sensing, storage, and computing. These cutting-edge technologies offer the potential to overcome the performance limitations of traditional architectures, significantly boosting computing power. This discussion explores the physical mechanisms, device structure, performance characteristics, and applications of RRAM devices. Additionally, we delve into the potential future adoption of these technologies at an industrial scale, along with prospects and upcoming research directions.

The influence of plastic pyrolysis oil on fuel lubricity and diesel engine performance.

This study investigates the viability of using plastic oils derived from High-density polyethylene (HDPE), Polypropylene (PP), and Polystyrene (PS) as alternative fuels for diesel engines. The research focuses on comparing the physical and chemical properties, fuel lubricity, engine performance, combustion characteristics, and exhaust emissions of these plastic oils. Analysis revealed that PS exhibits different fuel properties compared to diesel, with a carbon range distribution similar to gasoline, while HDPE and PP properties closely resemble diesel fuel. To prevent potential engine damage, PS was excluded from engine tests. PP displayed the best fuel lubricity, attributed to its higher kinematic viscosity and sulphur content, reducing direct friction. Diesel followed, with PS and HDPE in decreasing order of lubricity. Diesel's lubricity was influenced by the 7% palmitic methyl ester content in the fuel. In engine tests, HDPE demonstrated BTE similar to diesel, while PP exhibited lower BTE due to combustion retardation, leading to increased energy losses and higher BSFC. The combustion characteristics, in-cylinder pressure, and heat release rate of HDPE closely resembled diesel, while PP showed significantly delayed combustion due to low oxygen content and higher kinematic viscosity. Notably, NOX emissions from PP were lower than diesel and HDPE at all engine loads due to heat losses, resulting in a low in-cylinder temperature unsuitable for NOX emission. HDPE produced higher NOX emissions than diesel at low and middle loads due to its higher H/C ratio, promoting high thermal NOX formation. HC emissions from both HDPE and PP were higher than diesel due to increased fuel supply, hindering chemical bond breakdown. Similarly, CO emissions increased for HDPE and PP due to insufficient time for complete combustion, with HDPE producing more CO due to its heavy composites and lower cetane index. Smoke emissions from both HDPE and PP surpassed diesel, attributed to lower oxygen and higher sulphur content, leading to increased sulphurate particulate matter formation, and lower fuel density referring to the high amount of fuel supplied to the engine.

Adaptation of a Vanadium Redox Flow Battery for Thermal Applications Using a Solid Capacity Booster

In this work a novel approach for the use of the Vanadium Redox Flow Batteries (VRFB) is made by viewing it as a dual system with the ability to store both electrical and thermal energy. Electrical energy is thanks to the electrochemical reactions of the vanadium ions dissolved in the electrolyte, while thermal energy will use the sensible heat of the electrolyte mass.The performance of VRFB has been widely studied over the last 40 years and there is an extensive bibliography on the subject regarding the electrochemical performance attending only to the conventional energy storage requirements, but the hybrid electrical-thermal function is a novel subject that has been scarcely explored. One of the most critical aspects is the narrow operating temperature range of these batteries (15-40°C) that strongly limits their thermal energy storage capacity.Practical vanadium electrolytes operate with electrolytes containing a vanadium concentration between 1.6 and 2.0 M, and usually also employ cooling and heating systems to maintain the temperature between 15 and 40ºC. In particular, at temperatures below 15ºC the slower reaction kinetics, high viscosity and reduced conductivity of the concentrated electrolytes introduce remarkable energy losses in the battery. On the other hand, at temperatures over 35ºC the positive electrolyte is not stable due to the limited solubility of VO2 + species. High temperatures also boost the kinetics of parasitic reactions such as hydrogen and oxygen evolution, thus increasing energy losses.In this study, we address these limitations aiming to open up new possibilities of a successful integration of vanadium redox flow batteries into thermal applications. For this, the functionality and stability limits of a diluted vanadium electrolyte are analyzed for an extended operational temperature window from 5ºC to 50ºC and compared to commercial electrolyte formulations. In a second step, the use of a solid capacity booster is investigated to compensate the loss of energy density due to electrolyte dilution.[1] S. Berling, S. Mavrikis, N. Patil, E. García – Quismondo, J. Palma, C. Ponce de León “Lignin as redox-targeted catalyst for the positive vanadium electrolyte”, Electrochemistry Communications 142 (2022) 107339.[2] S. Berling, J. M. Hidalgo, N. Patil, E. García - Quismondo, J. Palma, C.Ponce de León, “A mediated vanadium flow battery: Lignin as redox-targeting active material in the vanadium catholyte”. Submitted

Reduced systolic flow efficacy in left ventricular dyssynchrony evident by blood speckle imaging

Abstract Introduction Intraventricular vortices facilitate efficient blood flow in a healthy heart. Changes in the blood flow pattern can cause energy loss and inefficient filling or ejection. Thus changes, or reduction in vorticity may therefore be of importance for cardiac function. Blood speckle imaging (BSI) is a novel blood flow visualization tool based on echocardiography, partially overcoming the angel dependency of conventional colour Doppler. BSI tracks speckles generated by the moving blood cells, similar to myocardial speckle tracking, but requires a very high frame rate limiting penetration. Dyssynchrony in left bundle branch block (LBBB) affects the systolic functions but there is limited insight into how LBBB alters the blood flow vorticity. Purpose We investigated the effect of dyssynchrony on blood flow hemodynamics using blood speckle imaging. Methods In eight anesthetized canine mongrels, left ventricular flow was visualized using BSI. A qualitative visual assessment of vortices during the cardiac cycle, together with a quantitative assessment based on kinetic energy loss and vorticity were made. Regional myocardial function parameters were measured by sonomicrometry. Peak septal flash strain in isovolumetric contraction (IVC) was measured by sonomicrometry (figure) as an indicator of dyssynchrony. Assessments were made at baseline, under right ventricular free wall pacing (RV pacing) mimicking LBBB, after induced LBBB by ablation and under cardiac resynchronization therapy (CRT). Results During IVC at baseline all animals had a central ventricular vortex. However during RV pacing and LBBB it was distorted in various patterns. RV pacing significantly reduced the number of vortices in systole and disrupted the central vortex in IVC (1.0±0.0 vs 0.4±0.5, p=0.01). Energy loss (EL) in systole increased (40.2±12.5 vs 55.3±23.3 mW/m, p&amp;lt;.05). Septal end systolic strain was significantly reduced (-8.8±5.1 vs -1.9±7.3 %, p&amp;lt;0.01) and septal flash strain was significantly increased (1.0±1.4 vs 7.7±3.6 and 6.6±3.8 [ER1] [ER2] %, p&amp;lt;0.01) in RV pacing and LBBB. CRT caused a realignment of the central vortex (0.8±0.5 vs0.3±0.5, p=0.03). The change in energy loss was not significant, but numerically reduced (55.4±38.8 vs 76.4±48.9 mW/m, p=0.06). See table and figure 1. Conclusions The main systolic vortex in IVC was disrupted during septal flash by RV pacing and LBBB, altering the flow pattern compared to baseline. The resultant unstructured flow pattern had increased energy loss in systole, indicating a less efficient flow pattern and less preservation of energy. It should be further explored if this is of importance to understand the reduced LV function and LV remodelling during dyssynchrony.Figure 1Table 1

Restoration of flow in the aorta: a novel therapeutic target in aortic valve intervention.

Aortic blood flow patterns are closely linked to the morphology and function of the left ventricle, aortic valve and aorta. These flow patterns demonstrate the exceptional adaptability of the cardiovascular system to maintain blood circulation under a broad range of haemodynamic workloads and can be altered in various pathophysiological states. For instance, normal ascending aortic systolic flow is predominantly laminar, whereas abnormal aortic systolic flow is associated with increased eccentricity, vorticity and flow reversal. These flow abnormalities result in reduced aortic conduit function and increased energy loss in the cardiovascular system. Emerging evidence details the association of these flow patterns with loss of aortic compliance, which leads to adverse left ventricular remodelling, poor tissue perfusion, and an increased risk of morbidity and death. In this Perspective article, we review the evidence for the link between aortic flow-related abnormalities and cardiovascular disease and how these changes in aortic flow patterns are emerging as a therapeutic target for aortic valve intervention in first-in-human studies.

Dynamic analysis of the joint movement of the hoisting and slewing mechanisms of a boom crane

To increase the productivity of boom cranes, the operation of individual mechanisms is combined. At the same time, dynamic loads on structural elements, drive mechanisms and loads on a flexible suspension increase, which reduces the reliability of crane operation and increases energy losses. Therefore, the research aims to consider the problem of the dynamics of the joint movement of the mechanisms for load slewing and hoisting of a boom crane. To study the dynamics of the joint movement of the mechanisms, the boom system was represented by a mechanical system with 6DOF, where the basic movement of the mechanisms and the oscillatory movement of the structural links with elastic and dissipative properties, as well as the load on a flexible suspension in the plane of crane slewing and hoisting were considered. For such a mechanical system of a crane, the differential equations of the joint motion of the crane slewing and hoisting mechanisms were developed. The obtained equations are a system of the second order nonlinear differential equations, for solving which a numerical method in the form of a computer program was used. Using the developed program, the dynamics of the joint movement of the mechanisms of a jib crane with specific numerical parameters were calculated. Based on the calculations, a dynamic analysis of the joint movement of the mechanisms for slewing and hoisting the load of a jib crane with a hoisting boom was carried out, which revealed high-frequency vibrations of links with elastic and dissipative properties, as well as low-frequency oscillations of the load on a flexible suspension. The greatest impact of oscillations is observed during the start-up of mechanisms, where high-frequency oscillations dampen during the transient process, and low-frequency oscillations dampen over a fairly significant period. To improve the dynamic properties of the mechanisms for turning and hoisting a load during their joint movement, it is proposed to optimise the mode of movement in the areas of transient processes (start-up, braking). The research results can be used in the development and operation of cranes in mechanical engineering, construction, and other industries

Probabilistic optimal planning of multiple photovoltaics and battery energy storage systems in distribution networks: A boosted equilibrium optimizer with time-variant load models

In recent years, there has been a rapid increase in distributed generation (DG) technologies incorporated into distribution networks (DNs) to meet the challenge of load growth. However, the stochastic nature of renewable energy, such as photovoltaic (PV), makes the amount of energy produced uncertain. This uncertainty, along with changes in generation and load demand, can increase energy losses and voltage instability. To address this issue, energy storage systems can be integrated to decrease the effects of the intermittency associated with renewable technologies. This paper proposes a new variant of an equilibrium optimizer (EO) based on reinforced learning, named RLEO, for optimal incorporation of multiple battery energy storage (BES) units integrated synchronously with solar PVs into distribution systems while minimizing energy loss. The RLEO algorithm employs reinforced learning mechanisms to prevent premature convergence of the EO and improve its exploration and exploitation capabilities. The performance of the RLEO algorithm is assessed using standard CEC 2017 benchmark functions and compared with the original EO and other popular algorithms using various statistical criteria. The RLEO algorithm is also applied to determine the optimal size and position of multiple PV units in IEEE 69-bus and 118-bus DNs with single and multi-objective optimization problems. Using the developed algorithm, the optimal arrangement of three non-dispatchable PVs results in a slight increase in the percentage reduction of energy loss across various load profiles: 53.0035 % for commercial, 19.6372 % for industrial, and 28.1783 % for residential. In contrast, by employing the optimal configuration of three PV + BES units, the reduction in energy loss percentage experiences a remarkable surge to 68.3466 % for commercial, 68.0917 % for industrial, and 68.1779 % for residential load scenarios using the proposed algorithm. This clearly indicates that the proposed RLEO algorithm significantly surpasses recent optimization methods documented in the literature when it comes to addressing the challenge of optimal allocation for multiple DGs. Furthermore, its applicability extends to more intricate optimization problems.

Biomechanical properties of the aortic root are distinct from those of the ascending aorta in both normal and aneurysmal states

BackgroundAlthough aneurysms of the ascending aorta and the aortic root are treated similarly in clinical guidelines, how biomechanical properties differ between these 2 segments of aorta is poorly defined. MethodsBiomechanical testing was performed on tissue collected from the aortic root (normal = 11, aneurysm = 51) and the ascending aorta (normal = 21, aneurysm = 76). Energy loss, tangent modulus of elasticity, and delamination strength were evaluated. These biomechanical properties were then compared between (1) normal ascending and normal root tissue, (2) normal and aneurysmal root tissue, (3) normal and aneurysmal ascending tissue, and (4) aneurysmal root and aneurysmal ascending tissue. Propensity score matching was performed to further compare aneurysmal root and aneurysmal ascending aortic tissue. Clinical and biomechanical variables associated with decreased delamination strength in the aortic root were evaluated. ResultsThe normal aortic root demonstrated greater viscoelastic behavior (energy loss 0.08 [0.06, 0.10] vs 0.05 [0.04, 0.06], P = .008), and greater resistance against delamination (93 [58, 126] mN/mm vs 54 [40, 63] mN/mm, P = .05) compared with the ascending aorta. Delamination strength was significantly reduced in aneurysms in both the root and the ascending aorta compared with their normal states. Aneurysms of the aortic root matched to the ascending aortic aneurysms in terms of baseline characteristics including size, were characterized by a larger decrease in delamination strength from baseline (Δ −59 mN/mm vs Δ −24 mN/mm). Aging (P = .003) and the presence of hypertension (P = .02) were associated with weakening of the aortic root, while diameter did not have this association (P = .29). ConclusionsThe normal aortic root was found to have distinct biomechanical properties compared with the ascending aorta. When aneurysms form in the aortic root, there is less strength against delamination, without other biomechanical changes such as increased energy loss observed in aneurysmal ascending aortas. Age and hypertension were associated decreased aortic wall strength in the aortic root, whereas diameter had no such association.

Greenhouse gas emission reduction potential, energy and exergy analysis of combined microwave-convective dryer

About 12–25% of the energy used in the food processing industries in the drying section and various technologies such as the combination of microwave and convective methods has been applied to reduce greenhouse gases and environmental pollution effects. In this study, the effects of microwave power (200–500 W) and drying air temperatures (30–55 °C) on energy and exergy aspects, GHG emissions (CO2, SO2, and NOx), and GHG reduction potential were evaluated and optimized using genetic algorithm approach in a combined microwave-convective drying process. The results showed that higher drying air temperature caused an increasing energy loss and decreasing exergy efficiency. The energy and exergy efficiencies were found to be in the range of 5.20–23.50% and 5.12–9.19%, respectively. The exergy improvement potential and GHG emissions decreased with increasing microwave power and decreasing drying air temperature. The total GHG emissions varied between 2002.4 and 7627.4 (g/kg water). Optimization of the drying parameters for the given constraints resulted in 498 W and 30.2 °C. The GHG emissions can be reduced 14.1%–28.6% with a recovery of exergy loss. Therefore, it can be concluded that heat recovery mechanisms are needed to reduce exergy waste and GHG emissions.

A Robust Control Strategy for the Automatic Load Commutation Device Considering Uncertainties of Source and Load

The long-term three-phase imbalance in distribution systems can lead to increased energy losses during transmission, reduced efficiency in energy utilization, and have serious implications for power supply security, power quality, and economic operations of the power system. The automatic load commutation device is an automatic device designed to address the issue of three-phase load imbalances in low-voltage distribution networks. By adjusting the phase of users without interrupting the power supply, this automatic device evenly distributes the load across all phases and effectively resolves the three-phase imbalance problem. Therefore, aiming at the above issue, a robust optimization method is adopted to address the control problem of automatic load commutation devices for a low-voltage distribution network. First, using historical data from photovoltaic and wind power generation systems as well as user load, a forecast analysis is conducted and uncertainty models for renewable energy and load demand are established. Then, a robust control strategy for the automatic load commutation device is proposed, which considers uncertainties of both source and load using the robust optimization method. The proposed model is then linearized using second-order cone technology and strong dual theory, and the column-and-constrained generation (C&amp;CG) algorithm is employed to solve the problem iteratively. Finally, a modified IEEE 33-bus system is taken to verify the effectiveness of the proposed strategy. The simulation results show that the proposed load commutation device robust control model can enhance the ability of the distribution network to respond to load demand and renewable energy fluctuations while ensuring the economic operation of the distribution network. In addition, by adjusting the deviation amount and uncertainty parameters of load demand and renewable energy, a good balance between the robustness and economy of the proposed model can be achieved.