Load Operation Research Articles

Transport helicopter blade root cuff attachment modernization concepts

The article discusses the issue of modernizing the blade root cuff attachment of the main rotor blade of a Mi-8 type transport helicopter. Several geometry options were designed and the stress-strain state of various options in a nonlinear formulation under the influence of operational loads was calculated using numerical methods. Conclusions are provided regarding the strength and mass of the blade root cuff attachment options under consideration. The influence of the tightening value of fasteners and the use of adhesive on the stress distribution along the connection is analyzed. Analytical methods were used to determine the optimal dimensions of fastening elements.

Enhancing renewable energy utilization and energy management strategies for new energy yachts

Hydrogen energy, due to its clean and efficient nature, has shown great potential during the current transition period in the shipbuilding industry. However, the application of hydrogen energy in ship energy systems is influenced by variations in operational load and the integration of new energy sources during actual navigation. To address these issues, this paper focuses on optimizing and scheduling the operation of ships under various navigation conditions, considering the distributed nature of hydrogen energy. System simulations were conducted to model the photovoltaic (PV), proton exchange membrane fuel cells (PEMFCs), lithium batteries (LIBs), electrolytic cells (ECs), and energy storage modules of yacht energy systems. Component boundaries and objective functions were set, and two cases (excess photovoltaic state and constant power state) were designed to optimize and regulate the energy balance of hydrogen-powered yachts, enhancing their comprehensive utilization of renewable energy. By comparing the changes in ship energy under the two cases, it was concluded that case 1 ensures the maximum utilization of renewable energy. When photovoltaic power generation is insufficient, the PEMFC and LIB in the system provide the required power to achieve a supply-demand balance. Moreover, when PV power generation is sufficient, hydrogen energy is used to store renewable energy. The optimization method designed in this study can, to some extent, maximize the application of renewable energy in new energy yachts, ensuring the efficiency of the comprehensive energy system of new energy yachts, reducing emissions, and improving the sustainability and economic efficiency of the ships.

Study on intelligent tyre force estimation algorithm based on strain analysis

The objective of this paper is to propose a novel approach to develop an algorithm for estimating the grounding force between a tyre and the road surface. First, a finite element model of a heavy-duty tyre is developed in this paper, and the validity of the model is verified by load application tests and mechanical vibration tests. When the tyres are operated under various operating conditions, that is, load, side deflection, side tilt and longitudinal slip conditions, the sensitivity analysis is performed by combining the three-directional forces based on the strain curves measured when the tyres are rolling, respectively. In order to achieve accurate estimation of the three-directional forces, this paper establishes a three-directional force estimation model using the support vector machine (SVM) technique, with the tyre force-sensitive eigenvalues as inputs and the tyre forces as outputs, so as to achieve the three-directional force estimation of the tyre-grounded three-directional forces. joint estimation of tyre-road contact force. The results show that the estimation error of vertical force is 1.79%, the estimation error of lateral force is 3%, the estimation error of longitudinal force is 4.65% and in general, the estimation error of grounding force is kept within 5%, and the estimation effect is good.

Synthesis, characterization, and optimization of dual‐responsive PAMAM nanodendrimers for improved dispersive solid‐phase extraction of cancer agents from complex biological samples

AbstractLevels of anticancer agents in cancer patients' body fluids are typically measured to adjust drug dosages or improve treatment results. The goal of this research is to present a new method for extracting bicalutamide (BCT) from biological samples using a responsive polymeric nanoadsorbent that reacts to temperature and near‐infrared radiation (NIR). To achieve this, the surface layers of tungsten disulfide nanosheets are modified using poly (N‐vinylcaprolactam) and three generations of polymeric dendrimers. The adsorbent product is then characterized using thermogravimetric analysis, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, and X‐ray diffraction techniques. The drug loading operation on the proposed adsorbent is studied through central composite design and response surface strategy, with optimization for temperature (25–45°C), pH (5–9), and contact time (2–18 min). Nonlinear kinetic and adsorption isotherm analysis results show the best fit with Langmuir and pseudo‐second‐order models. The drug release process from the BCT‐loaded adsorbent is investigated via an HPLC‐UV system under both NIR‐irradiated and non‐irradiated conditions. The suggested method demonstrates remarkable recovery rates for BCT spikes from urine (95.23%) and plasma (93.33%), respectively. Overall, the recommended strategy can be regarded as a potent analytical tool for evaluating BCT in complex biosamples.

Optimal Scheduling of the Active Distribution Network with Microgrids Considering Multi-Timescale Source-Load Forecasting

Integrating distributed generations (DGs) into distribution networks poses a challenge for active distribution networks (ADNs) when managing distributed resources for optimal scheduling. To address this issue, this paper proposes a day-ahead and intra-day scheduling approach based on a multi-microgrid system. It starts with a CNN-LSTM-based generation and load forecasting model to address the impact of generation and load uncertainties on the power grid scheduling. Then, an optimal day-ahead and intra-day scheduling framework for ADN and microgrids is introduced using predicted generation and load information. The day-ahead scheduling is responsible for optimizing the power interactions between ADN and the connected microgrids, while intra-day scheduling focuses on minimizing the operational costs of microgrids. The effectiveness of the proposed scheduling strategy is verified via case studies performed on a modified IEEE 33-node ADN. The results show that the network loss of ADN and the operation costs of microgrids are reduced by 17.31% and 32.81% after the microgrid is integrated into the ADN. The peak-valley difference in microgrids decreased by 13.12%. The simulation shows a significant reduction in operational costs and load fluctuations after implementing the proposed day-ahead and intra-day scheduling strategy. The seamless coordination between the day-ahead scheduling and intra-day scheduling allows for the precise adjustment of transfer power, alleviating peak load demand and minimizing network losses in the ADN system.

Optimized Frame Design for Head Loss Testing Equipment Through Material Strength Analysis

This article presents the design and analysis of a frame for head loss testing equipment, crucial for evaluating flow losses in pipe installations. The objective was to develop a robust yet lightweight frame that could withstand the operational loads imposed by the testing equipment. The frame, which supports essential components such as pipes, venturi meters, elbows, and reducers, was constructed using ASTM A500 hollow sections with dimensions of 20 x 20 x 1.6 mm and 35 x 35 x 1.6 mm. These dimensions were selected for their balance between strength and weight, validated through strength analysis and SolidWorks simulations. Conducted at Universitas Mercu Buana, the project involved the design, manufacturing, and testing of the frame to determine its load-bearing capacity. The results from the SolidWorks simulations confirmed the frame's structural integrity, which was further validated by its successful application in a practical setup. This study demonstrates the effectiveness of a systematic design approach, integrating material selection, load analysis, and simulation to achieve an optimal solution. The findings contribute valuable insights into the use of ASTM A500 hollow sections in structural applications, particularly where both strength and weight are critical. This work sets a precedent for future designs in mechanical engineering, offering a reliable framework for developing durable and efficient testing equipment.

Experimental research on wide load operation characteristics of circulating fluidized bed under the action of high-temperature activated gas-solid binary fuels

The circulating fluidized bed (CFB) units, with their robust combustion stability under low load conditions, are poised to play a significant role in future deep peak shaving of power grids. However, issues such as NOx emissions exceedance arise when the CFB unit operates for deep peak shaving. To mitigate these problems, this paper innovatively proposes a CFB coal blended with the high-temperature activated gas-solid binary fuel combustion mode to reduce the NOx emissions of the CFB across a wide load range. The wide load operation characteristics of the CFB under the action of high-temperature activated gas-solid binary fuel were initially examined on a 2 MW experimental platform. A comparison between the conventional combustion mode and the CFB coal blended with high-temperature activated gas-solid binary fuel combustion mode revealed that the latter improved the uniformity of temperature distribution within the CFB across a wide load range, particularly at lower loads. Furthermore, the CFB coal blended with high-temperature activated gas-solid binary fuel significantly reduced the original NOx emissions, decreasing from 136.9 mg/m3, 37.5 mg/m3, and 38.8 mg/m3 to 92.0 mg/m3, 24.7 mg/m3 and 20.6 mg/m3 at 100 %, 50 %, and 30 % load respectively, thereby achieving ultralow original NOx emissions during deep peak shaving operations. However, there is room for improvement in enhancing combustion efficiency using this combustion mode.

Analisis Kerusakan Diafragma Suling Pada Lokomotif Menggunakan Metode Fishbone Diagram

The analysis of the flute diaphragm damage in the locomotive was carried out using the Fishbone Diagram method to identify and group the main cause of the damage. This method visualizes the various factors that contribute to the problem through fishbone diagrams, allowing for an in-depth understanding of the relationship between causative factors such as design, materials, operational processes, and maintenance. The results of the analysis show that the damage to the distilled diaphragm is affected by a combination of internal and external factors, including material wear, excessive operational load, and lack of regular maintenance. These findings provide a basis for formulating more effective repair and prevention strategies, thereby improving the reliability and longevity of components in locomotives.

Implementation of 4-bit Universal Shift Register using Reversible Logic

The field of digital logic design is increasingly exploring reversible logic due to its potential in minimizing power dissipation, an essential criterion in low-power applications. This paper presents the design and implementation of a 4-bit universal shift register (USR) using reversible logic gates. The design leverages Fredkin gates, multiplexer (MUX), and D flip-flops to achieve functionality with minimal power consumption. Simulation results demonstrate the efficiency and effectiveness of the proposed design. Reversible logic is essential to low-power digital design and quantum computing because it makes it possible to reconstruct input signals from output signals, which reduces heat generation and information loss. The suggested shift register can be used for hold, parallel load, and left and right shift operations. To implement the functions of the shift register, we used a variety of reversible gates, including the Toffoli and Fredkin gates. When the architecture is contrasted with traditional non-reversible shift registers, it shows notable gains in reduced gate count and power efficiency

Experimental and Numerical Analysis of an Innovative Combined String–Cable Bridge

Suspension bridges, such as stress-ribbon, are among the simplest structural bridge systems and have the lowest structural height. The flexibility of these elegant bridges poses great challenges for designers to minimize their deformability under asymmetrical operational loads. Due to the small initial sag, such load-bearing structures also cause significant tensile forces, which requires them to have large cross-sections and massive anchor foundations. This paper analyzes an innovative suspension steel bridge structure combined with a string and a cable. More attention is paid to asymmetric loading as this is more relevant for suspension structures. The new structure is studied numerically and experimentally. It is established that the string stabilizes the displacements of the bridge under asymmetric loading. The stabilization efficiency is proportional to the value of the pre-tension force of the string. The obtained results reveal the behavior of the structure and enable an evaluation of the accuracy of the numerical results, as well as the applied modeling. In addition, the experimentally obtained results allow the evaluation of more aspects of the behavior of the new bridge, which will be useful in further studies of this type of structures.

Cryogenic Insulation-Towards Environmentally Friendly Polyurethane Foams.

Cryogenics is the science and technology of very low temperatures, typically below 120 K. The most common applications are liquified natural gas carriers, ground-based tanks, and propellant tanks for space launchers. A crucial aspect of cryogenic technology is effective insulation to minimise boil-off from storage tanks and prevent frost build-up. Rigid closed-cell foams are prominent in various applications, including cryogenic insulation, due to their balance between thermal and mechanical properties. Polyurethane (PU) foam is widely used for internal insulation in cryogenic tanks, providing durability under thermal shocks and operational loads. External insulation, used in liquified natural gas carriers and ground-based tanks, generally demands less compressive strength and can utilise lower-density foams. The evolution of cryogenic insulation materials has seen the incorporation of environmentally friendly blowing agents and bio-based polyols to enhance sustainability. Fourth-generation physical blowing agents, such as HFO-1233zd(E) and HFO-1336mzz(Z), offer low global warming potential and improved thermal conductivity. Additionally, bio-based polyols from renewable resources like different natural oils and recycled polyethylene terephthalate (PET) are being integrated into rigid PU foams, showing promising properties for cryogenic applications. Research continues to optimise these materials for better mechanical performance and environmental impact.

Hybrid operational modal analysis of an operative two-bladed offshore wind turbine

As with any strategic structure, vibration-based structural health monitoring techniques are often used to ensure the structurally safe operation of offshore wind turbines. Among such techniques, Operational Modal Analysis (OMA) methods allow the identification of modal properties, such as natural frequencies, mode shapes and damping, which variation might be caused by damage or operational/environmental factors. This paper investigates the application of OMA techniques on a two-bladed offshore wind turbine, which poses multiple challenges: fundamental OMA assumptions about the applied loads are violated by environmental and operational loads; the closely spaced modes of an offshore wind turbine are hard to identify; and an operative two-bladed offshore wind turbine is a time-variant system. Within this study, three OMA procedures to overcome some of the preceding challenges are discussed: (1) a standard frequency domain decomposition method; (2) a proposed enhanced transmissibility-based approach with a post-processing technique based on the Kurtosis index; and (3) a proposed refined hybrid OMA procedure that combines a transmissibility-based approach, the dedicated post-processing technique based on the Kurtosis index, and the frequency domain decomposition method. A numerical model representative of an operative two-bladed offshore wind turbine is used to compare the three procedures. Based on the comparison, the hybrid method is proven to be a promising new OMA-based procedure that outperforms the stand-alone transmissibility-based approach and the frequency domain decomposition method in identifying the modal properties of a two-bladed offshore wind turbine.

Optimal Scheduling of Island Microgrids with Seawater Pumped Storage Plants for Multi‐Energy Complementarity

The rapid development of new energy sources, such as offshore wind power and photovoltaic power, has provided a new solution to the problem of power supply for islands far from the mainland. Wave energy is a kind of renewable energy originated from the ocean, but the existing island power supply programs seldom consider this favorable natural condition. In addition, seawater variable‐speed pumped storage is a new idea to consume offshore wind power and improve the reliability of coastal and island power systems. In view of the stochastic and intermittent nature of new energy sources, this paper adopts seawater variable‐speed pumped storage power plants as energy storage equipment, and put forward an island power supply scheme with wind power, photovoltaic power generation, wave power generation, pumped storage power plants and diesel generator sets as a multifunctional complementary isolated grid. Firstly, wave energy generators, wind farms, photovoltaic farms, pumped storage power stations and diesel generator sets are modeled separately. Then, considering their respective operating conditions, constraints and load requirements, the optimal scheduling of island microgrids with multi‐energy complementarity is constructed. Finally, based on the improved particle swarm optimization algorithm, the model is solved. According to the wind power photovoltaic and wave power output curves of several typical scenarios in an island far away from the mainland, the cost and benefit of different schemes are compared to verify the effectiveness of the optimal scheduling in this paper. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Enhancing reactivity-controlled compression ignition engine performance: A response surface methodology approach with ammonium hydroxide-waste cooking oil biodiesel optimization

The focus on ammonium hydroxide, biodiesels and their combustion technology has garnered significant attention in pursuing carbon-neutral and carbon-free fuels to address greenhouse gas emissions (GHG) and mitigate global warming. Low-temperature combustion (LTC) has been introduced as an alternative method to conventional compression ignition (CI) combustion. Reactivity controlled compression ignition (RCCI) can be achieved by introducing highly reactive waste cooking oil methyl ester (WCOME) oil directly into the manifold in intervals of 10% energy and injecting low-reactive ammonium hydroxide at 20%–50%. Utilizing the response surface methodology (RSM) approach, it was determined that for optimal operation in RCCI mode, an ideal ammonium hydroxide energy sharing (AHES) of 43% would account for the varying parameters and their effects on emissions and performance. The results of the experiments predicted a brake thermal efficiency (BTHE) of 34.85% and a brake specific energy consumption (BSEC) of 10.69 MJ/kWh. Meanwhile, a notable decrease in exhaust emissions was observed for HC, CO, CO2, NO x and smoke by 41.54%, 38.89%, 48.89%, 51.27% and 65.80% respectively when compared to conventional biodiesel combustion (CBC). The experimental result at maximum load operation with an AHES of 50% indicates that RCCI combustion led to an increase in thermal efficiency from 30.36% to 35.42%, and the in-cylinder pressure and heat release rate dropped from 83.42 bar to 59.64 bar and 78.68 kJ to 60.92 kJ, respectively. There was a significant reduction in HC, CO, CO2, NO x and smoke emissions recorded as 58.76 ppm, 0.11%v, 1.61%v, 442 ppm and 6.64 N, respectively, compared to CBC.

Energy Scheduling in the Multiple Energy System with Optimal Operation of the Responsive Loads

Energy Scheduling in the Multiple Energy System with Optimal Operation of the Responsive Loads

Novel load allocation analysis for energy management and carbon emissions reduction of chiller system in hotel buildings

The operation of chiller systems for cooling energy generation in hotel buildings consumes the highest proportion of electricity. This study aims to introduce load allocation analysis to assess the potential for energy savings by a chiller system. The cooling load profile of a hotel in a subtropical climate is simulated using EnergyPlus. Eleven design options for the system include 4 to 8 chillers of the same or different capacities. Restoring chiller sequencing with high load operation can reduce the system's energy use intensity (EUI) by 12.7 %. An optimal design of four large and two small chillers with proper sequencing can reduce the EUI by up to 26.82 % or carbon emissions by 551,516 kgCO2-e. Increasing capacity steps above ten brings no significant energy savings and imposes complicated chiller staging. The area of the load allocation region can be evaluated simply from the chiller system design and used to analyze the system's energy performance. The EUI can be reduced by 0.3261 % for a 1 % drop in the area of load allocation region. The novelty of this study lies in using the load allocation region to assess energy savings of a chiller system without referring to sophisticated operating data at short timesteps. The significance of this study is to highlight the limitations of energy savings from the optimum chiller system design and address the need for incorporating more low energy technologies to enhance decarbonization.

Multi-objective multi-population simplified swarm optimization for container loading optimization with practical constraints

The container loading problem (CLP) holds significant importance in logistics and supply chain management due to its direct influence on transportation costs and times, thereby impacting the competitive advantages of enterprises across industries. Although there are existing studies for CLP, there remains a gap in addressing the optimization of multiple objectives while satisfying practical constraints. Moreover, container loading methods must also meet performance requirements such as high computational speed, explainability, and implementation capability. Although meta-heuristic-based algorithms have shown effective computational capabilities and performance, such algorithms often being trapped in the local optima especially when searching in the vast solution space of the CLP, particularly as the quantity and diversity of cargo sizes and shapes increase. Motivated by realistic needs, this study aims to develop a UNISON-based framework that integrates the merging spaces algorithm, a novel simple but effective hybrid simplified swarm optimization genetic algorithm (SSO-GA), and a multi-populations co-evolution strategy to determine the loading sequence of parcels to maximize space utilization and weight balance while satisfying to practical constraints. Specifically, the merging spaces algorithm merges fragmented small spaces resulting from loaded parcels into larger spaces, thereby facilitating the accommodation of additional parcels. The hybrid SSO-GA splits encoded solutions and updates segment using novel strategies resulting in the rearrangement of a group of parcels and their corresponding layouts for better space utilization. Furthermore, the multi-populations co-evolution strategy enhances the diversity of the search space and stabilizes solution quality by simultaneously exploiting the best solutions and exploring alternative solutions during the solution update process. An empirical study was conducted by using a public benchmark dataset which demonstrated the practical effectiveness of the proposed framework by significantly improving average space utilization while ensuring center balance and satisfying practical constraints. Furthermore, this study can also serve as a digital support system capable of assisting decision-makers in optimizing container loading operations, thereby improving productivity and saving valuable time.

Ratchet loading and multi-ensemble operation in an optical lattice clock

We demonstrate programmable control over the spatial distribution of ultra-cold atoms confined in an optical lattice. The control is facilitated through a combination of spatial manipulation of the magneto-optical trap and atomic population shelving to a metastable state. We first employ the technique to load an extended (5 mm) atomic sample with uniform density in an optical lattice clock (OLC), reducing atomic interactions and realizing remarkable frequency homogeneity across the atomic cloud. We also prepare multiple spatially separated atomic ensembles, and realize multi-ensemble clock operation within the standard one-dimensional (1D) OLC architecture. Leveraging this technique, we prepare two oppositely spin-polarized ensembles that are independently addressable, offering a platform for implementing spectroscopic protocols for enhanced tracking of local oscillator phase. Finally, we demonstrate a relative fractional frequency instability at one second of 2.4(1)×10−17 between two ensembles, useful for characterization of intra-lattice differential systematics.

Detecting Transitions from Stability to Instability in Robotic Grasping Based on Tactile Perception.

Robots execute diverse load operations, including carrying, lifting, tilting, and moving objects, involving load changes or transfers. This dynamic process can result in the shift of interactive operations from stability to instability. In this paper, we respond to these dynamic changes by utilizing tactile images captured from tactile sensors during interactions, conducting a study on the dynamic stability and instability in operations, and propose a real-time dynamic state sensing network by integrating convolutional neural networks (CNNs) for spatial feature extraction and long short-term memory (LSTM) networks to capture temporal information. We collect a dataset capturing the entire transition from stable to unstable states during interaction. Employing a sliding window, we sample consecutive frames from the collected dataset and feed them into the network for the state change predictions of robots. The network achieves both real-time temporal sequence prediction at 31.84 ms per inference step and an average classification accuracy of 98.90%. Our experiments demonstrate the network's robustness, maintaining high accuracy even with previously unseen objects.

Detection of indentation damage in carbon fiber/epoxy composites via EIT during the application of bending loads

Electrical impedance tomography (EIT) is a method of spatially mapping the conductivity distribution of a domain and has been studied as a potential embedded sensing or nondestructive evaluation (NDE) tool. An often touted advantage of EIT is that it can be used in-situ; that is, because the method only requires the application of unobtrusive electrodes, it can conceivably be used while the component or structure is in operation. This material-as-the-sensor philosophy strongly aligns with key components of the NDE 4.0 vision such as the realization of intelligent cyber–physical systems (CPS) and digital twins. To date, however, the claim of in-situ sensing via EIT has not been significantly substantiated. This is problematic because operational loads induce strains that often change the conductivity of the material. Establishing that EIT can detect damage-induced conductivity changes through the presence of unrelated strain-induced conductivity changes is therefore important. To that end, we herein study the application of EIT for detecting indentation damage in a carbon fiber/epoxy composite as the composite is loaded in a four-point bend. It was found that the bending load changes the contact impedance of the electrodes, which resulted in poor EIT images when solving the EIT inverse problem with the ℓ2-norm on the error term. Using the ℓ1-norm on the error term, solved via the primal–dual interior point method (PDIPM), significantly improved image quality. Image quality was even further improved through the use of a mixed prior for regularization, and EIT images were compared to thermography with good agreement. These results show that EIT can indeed detect damage through the presence of an applied load, but care must be taken to account for factors such as outlier data arising from electrode degradation and changing contact impedance. Use of the ℓ1-norm on the error term is therefore highly recommended for in-situ imaging via EIT.