Load Control Research Articles

Clinical, Histological, and HPV-Related Factors Associated to Diffuse Presentation of Exophytic Nasal Papillomas

Background: Sinonasal exophytic papillomas (SNEP) are benign tumours arising from nasal mucosa. Human papillomavirus (HPV) infection seems to be related to the aetiology of a fraction of SNEP cases. SNEP presentation can be focal (FSNEP) or diffuse (DSNEP), but factors related to focal or diffuse presentation have not yet been well ascertained. This study aimed to analyse clinical, histological, and HPV-related differences between FSNEP and DSNEP. Methods: A retrospective cohort of 18 patients with SNEP from our centre were evaluated. Demographic, clinical and follow-up data were collected. All samples were subject to histopathological evaluation, DNA quality control, HPV-DNA detection, and viral load assessment. Univariate analyses were performed to evaluate differences between FSNEP and DSNEP. Results: Twelve SNEP patients were included in the final analysis. Seven patients had a diffuse nasal presentation, being younger than patients affected with FSNEP (42.7 years vs. 65.2 years, p = 0.019). The nasal septum was significantly more affected in DSNEP than in FSNEP (85.7% vs. 20%, p = 0.029). HPV-DNA was detected more frequently (100%) in DSNEP (HPV11 in six cases, HPV6 in one case) than in FSNEP (40%, p = 0.045, HPV6 in two cases). The median viral load among HPV6-positive samples was 626.8 virus/cell for FSNEP and 80.2 for DSNEP, and among HPV11-positive samples was 1673.7 for DSNEP. Recurrences were more frequent in the diffuse than in the focal group (85.7% vs. 20%, p = 0.029). Conclusions: The diffuse presentation of SNEP seems to be related to younger patients, nasal septum involvement, HPV infection, mostly HPV11, and a higher risk of recurrence.

A Universal Target Plate Design Scheme for Stellarators: theoretical basis and its application to heat load control

Abstract This study introduces a novel divertor target design scheme for stellarators, grounded in mathematical treatments and tailored to control toroidal heat load distributions. Initially, a differential equation characterizing toroidally uniform heat load distribution has been established in a two-dimensional (2D) slab configuration, and its analytic solution has been obtained. Subsequently, a numerical scheme has been developed to adapt the analytic solution into the 3D surface shape of stellarator target. The effectiveness of this design scheme has been validated through simulations of the Chinese First Quasi-axisymmetric Stellarator (CFQS) using a suite of codes including HINT, FLARE and EMC3-EIRENE, where a toroidally uniform heat load distribution has been achieved with an island configuration. Further, the effects of input parameters on the target shape and heat load distribution have been studied. The robustness of the designed target has been investigated by simulation results with varying magnetic island configurations, confirming that the toroidal uniformity of heat load distribution is insensitive to changes in island configurations. Moreover, the designed target has been assessed with gas puffing of neon, which shows that neon injections effectively reduce the heat loads without altering the toroidal uniformity of heat load distributions. The proposed scheme highlights the importance of theoretical and mathematical foundations of target design, offering an advantageous alternative/complement to the traditional numerical schemes.

Effect of Cyclic Load Frequency on the Fatigue Crack Nucleation and Growth of Annealed and Prestrained Austenitic SS 304

ABSTRACTThe austenitic stainless steels are widely used in several engineering fields due to their high ductility, corrosion and high temperature performance. Despite its noble properties, components manufactured in austenitic stainless steel are subject to fatigue failure. Studies indicate that loading frequency can impact the austenitic stainless steel fatigue performance. In this scenario, the present study aims to evaluate the effect of frequencies of 3 and 30 Hz on the fatigue behavior of SS 304 alloy under load control in order to identify in which fatigue stage the effect is outstanding. Therefore, fatigue and fracture mechanics tests were evaluated on the alloy annealed at 1000°C. Furthermore, fatigue tests were also applied to the alloy after previous tensile plastic strain of 0.5. The analyses denoted a significant reduction in fatigue strength with increasing frequency, especially for the strained alloy. Fatigue crack nucleation is encouraged with greater load frequency. This behavior may be attributed to strain‐induced martensite and other strain mechanisms such as twinning and slip bands that are encouraged by lower strain rates but are relieved by auto‐heating achieved in higher frequencies, as mentioned in the literature, which decrease the strength to fatigue nucleation.

A 4D Soil-Structure Interaction Model Testing Apparatus

Abstract A new three-axis loading frame has been developed to enable real-time visualization of in-situ soil and rock structure interactions via X-ray tomography during small-scale model testing. The constructed frame is capable of performing a wide range of small-scale 1g tests and can accommodate monotonic and cyclic actuation under both load and displacement control. The compact size of the system enables remote multi-axis operation from within an X-ray cone-beam scanning bay, a capability which is owed to a comprehensive design process. Design and fabrication involved a blend of physical and numerical experiments to assess suitable construction materials and performance. In this scope, the new equipment is discussed and its capability is showcased.

Individual differences in acceptance of direct load control

Individual differences in acceptance of direct load control

Multi-objective design of fractional frequency-load control for hydro-thermal system considering nonlinear models and uncertainty

One of the crucial quantities in the power system problem is frequency, which should never exceed its nominal value. In normal conditions of load changes, the frequency is adjusted by automatic generation control. Still, in the face of special conditions, such as logging of the downstream network from the main network or a significant amount of generated power leaving the circuit, the power imbalance between generation and consumption causes a rapid frequency drop. In this case, the automatic generation control cannot stop the frequency drop, so the frequency tends toward instability. In this paper, to automatically produce a water-thermal system in two zones of discrete and continuous modes, the design of a fractional controller is discussed and investigated in different functional conditions and uncertainties. The proposed NSGA-II multi-objective method is used in this article to optimize each area’s load frequency control parameters for various goals. The ideal response for the entire network will be obtained by modifying these responses using a multi-factor method. This paper defines a multi-zone frequency load control based on time objective functions and eigenvalues. Based on the speed changes for the proposed algorithm and the novel approachfunction method employed in the control design. The simulation performed and analyzed in different working conditions with different comparative criteria has been discussed and investigated. Compared to more contemporary techniques, the simulation results show that the system’s performance is guaranteed. The main successes of the suggested method in comparison to earlier methods have been the reduction of overshoot, undershoot, and settling time.

Energy management and demand side management framework for nano-grid under various utility strategies and consumer’s preference

This research proposes a day-ahead scheduling utilizing both demand side management (DSM), and Energy Management (EM) in a grid-tied nanogrid comprises of photovoltaic, battery, and diesel generator for optimizing the generation cost and the energy not supplied (at grid-outage). Wider terminology is introduced to combine both load controllability (considered in traditional DSM), and interval capability to accommodate additional loads defined as flexible, non-flexible, and semi-flexible intervals. Moreover, the user selection for EM or combined operation of EM with DSM at different degrees of interval flexibility is defined as user preference. In addition, three utility’s operations are considered denoted as fixed rate pricing (FRP), time-of-use (ToU) pricing, and FRP with grid-outage. Hence, the suggested framework utilizes the opportunities of generation diversity, the electricity pricing strategy, and the load flexibility. The obtained result show that, DSM with flexible intervals reduces the cost by 21.02%, 25.23%, and 18.15% for FRP, ToU, and FRP with grid-outage scenarios respectively. And cost reduction by 20.41%, 22.42%, and 17.81% for DSM with semi-flexible intervals and 16.24%, 21.15%, and 13.8% for DSM with non-flexible intervals. This cost reduction is associated with full utilization of renewable energy generation and reduction of the energy from/to battery which enhances its lifetime or reduces the required battery size during design stage for cost and provisions saving in flexible and semi-flexible intervals. A hybrid optimization technique of Moth-flame optimization algorithm, and Lagrange’s multiplier is proposed and confirms its effectiveness with detailed comparison with other techniques.

Construction method for novel power load management system detection environment based on model adaptive equivalence

With the focus on integrating large-scale clean energy, the requirements for demand-side load resource management and maintaining the power system's supply-demand balance have increased. New types of power load management are thus gaining importance. Considering the varied load management needs and response strategies across different scenarios, and taking into account essential network elements like topology and connectivity, a multi-level interactive architecture is established to support hierarchical load control networking models for energy flow. By leveraging statistical analysis and simulation deduction, this approach improves the comprehensive evaluation of load system indicators, particularly in scenarios with small sample sizes and significant randomness. This methodology contributes to more efficient power system management and enhances load control adaptability.

Dynamic strain distribution monitoring and fatigue damage analysis on a 100 kW wind turbine blade based on field aerodynamic measurements

Abstract Operation and maintenance (O&M) costs can account for 10%–20% of the total costs of electricity for a wind project. Structural health monitoring method is a form of preventive maintenance consisting of regular monitoring of the wind turbine components to detect potential faults. The strain measurements on the blades are typically used for load monitoring and damage detection, but only obtain a small amount of concentrated load information. In this work, a strain distribution monitoring method was proposed and validated based on aerodynamic measurements in the field. Then the contribution and evolution of the strain distribution from the aerodynamic load, gravity load, inertial load, and centrifugal load in the complex start-up process of the wind turbine were analyzed. The results shows that the mean value of the synthetic strain is mainly determined by the aerodynamic load and the centrifugal load, while the fluctuation amplitude is mainly determined by the gravity and the aerodynamic load. Furthermore, the fatigue damage of the blade root was evaluated based on strain extrapolation, rainflow cycle-counting algorithm, Goodman diagram and Miner’s linear superposition principle. It is found that the fatigue damage is generally greatest near the pressure side and suction side, and least near the leading edge and trailing edge. The strain distribution monitoring method can capture the location of maximum stress and the most severe fatigue damage on the blade, which are helpful for damage detection and load control, and further reduces O&M costs.

Semantic memory navigation in HIV: Conceptual associations and word selection patterns

Objective: This proof-of-concept study aimed to characterize semantic memory profiles in individuals with human immunodeficiency virus (HIV) and mild neurocognitive impairment. Method: Using a semantic relatedness task, we explored conceptual association and word selection patterns in people living with HIV (PLWH; n = 50) relative to people living without HIV (n = 46). We also studied whether word selection patterns in the PLWH group were associated with working memory capacity, cognitive flexibility and inhibitory control. Results: While accuracy did not differ between groups, PLWH produced significantly longer responses than controls (r = .32), with fewer hypernyms (d = .47), more troponyms (r = .37), and words that were more frequent (r = .39) and had more phonological neighbors (r = .22). These patterns survived covariation with participants’ cognitive status. None of these patterns correlated with measures of working memory, cognitive flexibility, inhibitory control or viral load (all correlation coefficients < .36). Conclusions: Together, these results suggest that PLWH might use alternative word finding strategies during semantic memory navigation, irrespective of the severity of other cognitive symptoms. Such findings contribute to the characterization of cognitive deficits in HIV and to the search for novel markers of the condition.

Optimising load control of multi-type air conditioning in demand-side management

ABSTRACT With the continuous expansion of renewable energy capacity and the increasing demand for thermostatically controlled loads in China, new challenges have arisen for maintaining power supply stability. This paper establishes a control model for the aggregation of different types of air conditioning loads. To improve unsatisfactory demand response outcomes, a novel incentive mechanism based on tracking the target load curve is proposed. Additionally, a cost model for air conditioning load aggregators and the regional grid operator, along with an implementation scheme for trading mechanisms, is also developed. Case simulations validate the effectiveness and rationality of the proposed incentive mechanism.

Grain size and sediment load control on channel migration patterns of the Ghaghara river from Faizabad to Deoria, Ganga plain, India

Grain size and sediment load control on channel migration patterns of the Ghaghara river from Faizabad to Deoria, Ganga plain, India

B-031 A new Ready to use Bio-Rad Quality Control to Streamline Daily Workflow

Abstract Background A comprehensive Quality Management System starts with performing a daily Quality Control (Q.C.) process. The daily Q.C. process monitors the Instrument’s optimal performance and detects shifts and trends. However, the existing traditional daily Q.C. process is not only prone to manual errors, but also time consuming, costly and labor intensive. We evaluated a Bio-Rad InteliQTM Load and go Quality Control that comes in a barcoded tube ready to be loaded. We monitored the workflow efficiency gained in comparison to the traditional quality control material that comes in glass vials. Methods We evaluated the new quality control material ready to load on the instrument. This new Q.C. (Bio-Rad InteliQ Assayed Multiqual Control - 3 levels) were processed in parallel with our routine Q.C. (Bio-Rad Assayed Chemistry Lyphocheck vials - 2 levels). We performed the evaluation on Abbott Architect c8000 Chemistry analyzers in our central Laboratory (NGHA-Jeddah). The Q.C. was stored frozen. Before testing it was thawed at room temperature as per the insert instruction. Over a 5 days period, in parallel with our routine quality control, we run the new Q.C. Two times per day for 33 analytes. We monitored the processing time difference between the new and current approaches. We monitored the stability of all the analytes in the tube after Two days and again after Five days. We also monitored the cost effectiveness, labor intensiveness, probability of operator error and the overall improvement in workflow and Turn Around Time. Results Over the evaluation period, we observed the following: - Saving 40 minutes in average per week only for chemistry Q.C (time spent in reconstituting, mixing and aliquoting old Q.C) - 100% reduction in waste of plastic consumables such as pipette and plastic tubes. - Save an average of 1.0 ml dead volume in every 5.0 ml old Q.C. vial (20% of the volume, hence saving 20% of the total Q.C. cost). The dead volume wasted due to aliquoting step using the old Q.C. - 100% Eliminated delays caused by operator error such as wrong reconstitution, inadequate mixing and wrong Q.C. aliquoting. Not needed for the InteliQ. - High score of staff satisfaction. - Stability of the 32 analytes was excellent except that of Co2, which deteriorated by 14% after Two days as indicated in the insert package. Co2 day five result deteriorated by 34%. Conclusions Bio-Rad InteliQ is easy to use. It saves time and cost. When combined with Unity Q.C. data management solution it can streamline Q.C. workflow, eliminate operator errors, reduce T.A.T. and increase the overall laboratory performance. It may also work optimally with Instruments that have on-board fridge for Q.C.

Development of ITER first wall heat load feedback control

Real-time monitoring and control of thermal loads on tungsten plasma-facing components is mandatory for ITER to avoid their overheating during plasma discharges. For the Start of Research Operations (SRO) phase, dedicated First Wall Heat Load Control (FWHLC) functions are included in the ITER Plasma Control System (PCS) to prevent the development of excessive plasma heat loads on the inertially cooled first wall (FW). In this work, we propose a FWHLC design with a model-based approach, which features a simplified thermal model for the FW armour. This control-oriented model simulates the thermal response of ITER FW to slow changes in plasma equilibrium and energy, which during ITER operation will be monitored by the real-time wide angle infrared camera system. This allows computationally efficient runs for rapid controller performance assessment but can also assist operation scenario design by pre-empting potential heat load issues. FWHLC is designed to react to measured and predicted FW temperatures overcoming predesigned limits with real-time variations of the plasma shape or auxiliary power references, aiming to reduce thermal loads before a premature plasma termination is required to protect the FW. The new scheme is tested in closed loop simulations, where perturbations to nominal ITER low current scenarios are introduced in the wall thermal model to trigger the response of FWHLC, supporting the effectiveness of the proposed policy.

Large-signal stability analysis of an islanded DC microgrid with constant power loads based on mixed potential function

Abstract In DC microgrids, power electronic converters are widely used to connect loads and renewable energy sources to generate different voltages. These loads operate as constant power loads (CPL) within a closed control loop. When voltage fluctuates, these loads display negative impedance characteristics, potentially leading to system instability. Therefore, the analysis of the impact of CPL on DC microgrids during large disturbances is crucial. This paper employs mixed potential theory to study the large disturbance stability of DC microgrids under CPL. Deriving the stability criterion for the system under significant perturbations reveals the impact of load types and control parameters on system stability and provides a detailed analysis of how specific system parameters affect stability. Consequently, the stability criterion can ensure the system’s stability under large disturbances without the need for repeated calculations and simulations. Simulation results verify the correctness of this stability criterion.

Hybrid building energy modeling method with parameterized prototype models and rapid calibration

Building energy models were widely used in building energy performance analysis and efficiency improvement, such as building demand response assessment and energy system optimization. However, building energy modeling was a time-consuming and complex process. Therefore, this paper proposed a hybrid building energy modeling method based on parameterized prototype models and rapid calibration. The main feature of the method was the rapid generation of target building energy models using the prototype building energy performance database. The parameterized prototype building energy model considered 13 uncertainty parameters. Based on the range of 13 uncertainty parameters, such as wall U-value and solar heat gain coefficient, 1000 simulations were performed by Monte Carlo sampling to generate the prototype building energy performance database. The target building energy model was quickly calibrated by learning from this database. It filtered the models that met the requirements based on the actual building measurement data. Based on this hybrid modeling method, the rapid modeling tool AutoBPS-Hybrid was developed in a ruby environment. Shopping mall buildings located in three different climate zones were selected as case studies for this study. The results showed that if only one building energy model meeting the percentage errors was needed, only 3–4 simulations were required. If it was necessary to match the real uncertainty parameter distributions, an average of about 53 simulations was needed. The building energy models were applied to plug load and lighting control in buildings. The shopping mall buildings in Harbin, Beijing and Chengdu could reduce energy consumption by 10.18–13.33 kWh/m2, 14.43–18.15 kWh/m2 and 11.54–14.69 kWh/m2 per year, respectively.

A review of the application development and key technologies of rotary engines under the background of carbon neutrality

Rotary engines possess advantages such as light weight, high power density, and strong fuel adaptability, which are essential for powertrain systems. They hold great potential in the field of power machinery. However, the development of rotary engines has been constrained by increasingly stringent emission regulations. Despite this, numerous scholars and institutions continue to optimize rotary engines, leading to a proliferation of related research. It is necessary to synthesize these findings to guide future promotion and application efforts. This review examines the current applications and development status of rotary engines globally. It summarizes the development of key technologies such as sealing techniques, rotor configurations, and ignition devices, which have achieved lower energy consumption and emissions. The suitability of rotary engines for automotive and unmanned aerial vehicle applications has also been reported. To further reduce carbon emissions, researchers have explored zero-carbon fuel rotary engines. Hydrogen-fueled rotary engines have demonstrated higher combustion efficiency. By integrating EGR, load control strategies, and ignition system layouts, they have addressed issues such as NOx emissions, knock, and leakage. The development of ammonia-hydrogen hybrid fuels is also a potential effective solution. Continuous innovative research indicates that, with their inherent advantages and the integration of alternative fuels and advanced ignition technologies, rotary engines have the potential to meet future energy and environmental requirements. This positions them as strong contenders in future diversified power systems.

Development and validation of intelligent load control for VRF air-conditioning system with deep learning based load forecasting

Variable refrigerant flow (VRF) air-conditioning systems have seen significant growth in Asia and its application is expanding globally. Despite the expanded application, most previous studies have focused on developing fault detection and diagnostics to achieve energy-efficient operations than on predicting power consumption. It's very difficult to predict the electrical consumption owing to its complex system configuration and various control strategies. A new control strategy is described for optimal adjustment of the desired target level based on time series forecasting using the optimized sequence to sequence model for VRF systems. Sequence to sequence (seq2seq) model with attention mechanism and Bayesian optimization is developed to predict accurate hourly and daily forecasts and rapid feedback control for fluctuating power consumption for VRF systems. The optimized seq2seq model is integrated into the intelligent load control (ILC). ILC can be used to manage VRF systems by dynamically prioritizing indoor units for curtailment using both quantitative inputs and qualitative rules. Overall, the results demonstrate that the deep learning based control allows coordination of the controllable loads of VRF systems in three commercial buildings. ILC with deep learning manages the power consumption within a desired target level, as well as indoor temperature reflecting the status of controlled indoor units, as objective functions of the control algorithm.

A Life Cycle Cost Comparison of Flexible Versus Rigidpavements in Nigeria: Case Study of Papalanto - Sagamu Road

The condition of roads in Nigeria, most of which are made from asphalt, is generally considered unsatisfactory. This has led to calls for a blanket switch from asphalt pavements to concrete pavements for new road construction. This study examines the characteristics and relative advantages of the two pavement types; and carried out the design and life cycle cost comparison of a case study road with heavy traffic and poor subgrade conditions. The results indicate that, the initial cost of construction is actually less for the concrete pavement by 12% when compared with the asphalt alternative, while the life cycle cost analysis further yielded an advantage of 36% for the concrete pavement. The paper therefore recommends that major roads, particularly those on the national and international transit corridor, being of heavy traffic, should be reconstructed as the need arises, as concrete pavements. The paper however further recommends that, axle load control should be enforced through the introduction of weigh bridges and that routine maintenance should mandatorily be carried out, as even the best constructed concrete pavements have failed due to lack of routine maintenance like clearing the road verges of weed and road sand and desilting of drainage structures

Energy Optimization Approach in Wireless Sensor Network

In recent years, the importance of routing protocols in wireless sensor networks and the Internet of Things has been demonstrated by the numerous studies that have been presented in this area. because it is crucial to the network's functionality and effectiveness. Among routing's main goals are lowering latency, enhancing reliability, and averting network collisions. Additionally, it can be claimed that the type of network routing affects service quality, network longevity, and network traffic load control. Thus, in order to lower routing error and boost network performance and efficiency, the firefly is employed in this study to identify the best information transmission path within the network. It is also employed to reduce energy consumption. Taking into account the ability of evolutionary algorithms to optimize specified objective functions, we attempted to lower the network's energy consumption. The network can enhance the number of sending packets with the beginning energy of 3 joules from 1480 rounds to 1798 rounds, based on the proposed algorithm's results. Additionally, by contrasting the approaches described in the same article, it was discovered that the suggested approach can send roughly 40.11% more packets than the RM-LB algorithm and 1.9573% more than the OMS-LB technique. Additionally, it was discovered that by raising the starting energy to 150 joules, the suggested technique outperformed the other two algorithms by 51.23% and 45.17%, respectively, and was able to lengthen the longevity. This was in comparison to the RM-LB method and the OMS-LB method.