Performance Of Operations Research Articles

Structural Designs Meet Optimality: Exploring Optimized LSM-tree Structures in a Colossal Configuration Space

Mainstream LSM-tree-based key-value stores face challenges in optimizing performance for point lookup, range lookup, and update operations concurrently due to their constrained configurations. They typically follow fixed patterns to specify the level capacity and the number of sorted runs per-level. This confines their designs to a restricted space, limiting opportunities for broader optimizations. To address this challenge, we consider a more flexible configuration that enables independent adjustments of the number of runs per-level, size ratio, and Bloom filter settings at each LSM-tree level. By carefully analyzing the cost of each operation based on the new design space, we unveil two critical insights for optimizing the tradeoff among the three operations. Firstly, achieving efficient point lookup requires a large last level. Secondly, there is a specific correlation between the number of runs per level and size ratio that is advantageous for overall update and range lookup performance. Based on these insights, we introduce Moose, a structure delivering an impressive overall performance for point lookup, range lookup, and update concurrently. Furthermore, we also introduce a new framework, Smoose, to navigate the design space for adapting specific workloads. We implemented Moose and Smoose on top of RocksDB and experimental results demonstrate that our proposed approach outperforms state-of-the-art LSM-tree structures across diverse workloads.

Nonlinear time-reversal interferometry with arbitrary quadratic collective-spin interaction

Abstract Atomic nonlinear interferometry has wide applications in quantum metrology and quantum information science. Here we propose a nonlinear time-reversal interferometry scheme with high robustness and metrological gain based on the spin squeezing generated by arbitrary quadratic collective-spin interaction, which could be described by the Lipkin–Meshkov–Glick (LMG) model. We optimize the squeezing process, encoding process, and anti-squeezing process, finding that the two particular cases of the LMG model, one-axis twisting and two-axis twisting outperform in robustness and precision, respectively. Moreover, we propose a Floquet driving method to realize equivalent time reverse in the atomic system, which leads to high performance in precision, robustness, and operability. Our study sets a benchmark for achieving high precision and high robustness in atomic nonlinear interferometry.

Evaluating the performance of intercity road freight transport: Double-frontier parallel network cross-efficiency model

Performance assessment of Intercity Road Freight Transport (IRFT) involve a complex set of considerations to ensure the efficient transportation of goods between their origins and destinations. Notably, Data Envelopment Analysis (DEA) models are often the preferred approach for conducting assessment studies that involve multiple inputs and outputs. Even though the conventional Cross-Efficiency (CE) technique addresses the limitations of DEA in producing comparable results, it still fails to consider the evaluation of internal system operations. The use of Network CE leads to more realistic results in assessing problems. It addresses not only the limitations of the DEA model in producing comparable results but also considers the performance of internal operations and system efficiency. Incorporating CE into a Parallel Network System (PNS), which is known as CE-PNS, has also a significant drawback as it neglects both the optimistic and pessimistic viewpoints based on the efficient and anti-efficient frontiers simultaneously, and may therefore fail to provide a comprehensive analysis. The primary objective of this study is to propose a new double-frontier network CE that takes into account two perspectives simultaneously. Indeed, this study is the first to incorporate the concepts of CE and double-frontier DEA into a PNS to provide an effective tool for assessing Iranian IRFT. For this purpose, the Cross-Inefficiency (CIE) technique is first incorporated into the PNS, called CIE-PNS, which explores the relationship between system inefficiency and internal divisions. The CE-PNS and CIE-PNS may yield different results. Therefore, Double-Frontier CE for a PNS (DFCE-PNS) is derived by combining the efficiency results obtained from CE-PNS and CIE-PNS. This study also examines different inputs and outputs to assess the performance of Iranian IRFT. The results demonstrate that DFCE-PNS yields more comprehensive and reliable results.

Designing of self balancing amplitude modulated five level inverter for reducing voltage stress gradients on converter switches for electric vehicles

The research article endeavors to explore the efficient multi-quadrant operations in Electric Vehicles (EV), which emphasizing among the renewable sources and Energy Storage Management Systems (ESMS). This coordination is facilitated through the latest advancements in converter circuits, aiming to enhance efficiency and performance in EV operations. The primary converting circuit, or inverter, is crucial in optimizing the utilization of energy sourced from renewable sources. The coordination among these systems along with the converter, produces harmonics, due to the shifting of operating modes in EV motors in quick sessions because of dynamic real-time road conditions. This research paper presents the design and implementation of Self Balancing Modulated Five-Level Inverter along with a powerful modulation technique and coordinated with the ESMS of electric car application. The proposed 5-Level inverter shows the reduction in torque distortions in an electric vehicle drives over conventional two-stage boost inverter (2SBI) circuits. The designed Five-Level Inverter (FLI) circuit characterized by reduced switching operations, shows a significant reduction in voltage stress gradients on switches and achieves self-balancing of voltages with reduced operating components. The developed three-phase boost single circuit named as SBAM-FLI is connected to the grid integrated renewable energy application and the system is tested at constant and variable torque conditions. A comparative analysis is conducted between the operation of self-balancing modulated FLI with 2SBI based on the obtained results and power loss analysis is performed for the performance evolution in EV applications. The proposed topology is adaptable to both the Trapezoidal and Sinusoidal Back EMF drive mechanisms, which shows significant improvement over conventional inverters. The experimental validation of proposed self-balancing modulated FLI design is presented in this research. The experimental setup was realized using Xilinx block sets and seamlessly integrated with the Basys-3 Artix-FPGA board, consequently, both the experimental and simulation outcomes of the proposed converter topology were validated and provides substantial impact on EV applications.

Повышение ресурса рабочих колес центробежных насосов шахтного водоотлива

Mining The article discusses the main failure causes of centrifugal pumps used in the mine dewatering plants. The factors causing intensive wear of the impellers used in centrifugal pumps of the CNS-33-66...330 type are analysed, as well as the ways of increasing their serviceability. The gas dynamic cold spraying is recognized as the most promising and efficient method of applying functional coatings, which makes it possible to improve the condition of the surface layer and eliminate surface defects of the initial impeller blanks, which have a significant impact on the serviceability of the parts. The main research trends are outlined in the studied area, and practical recommendations are provided on using the gas dynamic cold spraying methid both in the pump manufacturing process and in their overhaul. It is shown that one of the promising trends in development the gas dynamic cold spraying applications is the creation of multilayer coatings on the impeller blades based on compositions of various metal-ceramic powders. Along with the hardening treatment, this combination will allow to provide the impellers with a set of necessary functional characteristics for the hydro-abrasive wear conditions. technological process as a sequence of changing the natural state of the Earth's subsoil to obtain a certain quantity and quality of mineral products is characterized by departures from the specified normative parameter values, which is due to causes of different nature. Most of these causes are man-made, anf they are created during the performance of specific process operations by the personnel. The article presents an original approach to managing the control over the technological process parameters in a coal strip mine. To reduce the magnitude and probability of the process departures from the normative values, the authors propose to create technical and organizational control loops. Each loop is a closed chain of technical means and organizational tools, which secures up-keeping of the normative technological process state. Production risk is proposed to be used as a criterion to assess the efficiency of the control loops. The methodology allowing to calculate the risk is described. The results of the contour approach application to the technological process control at the Solntsevsky coal strip mine are presented.

Формирование контуров контроля технологического процесса угольного разреза

Mining technological process as a sequence of changing the natural state of the Earth's subsoil to obtain a certain quantity and quality of mineral products is characterized by departures from the specified normative parameter values, which is due to causes of different nature. Most of these causes are man-made, anf they are created during the performance of specific process operations by the personnel. The article presents an original approach to managing the control over the technological process parameters in a coal strip mine. To reduce the magnitude and probability of the process departures from the normative values, the authors propose to create technical and organizational control loops. Each loop is a closed chain of technical means and organizational tools, which secures up-keeping of the normative technological process state. Production risk is proposed to be used as a criterion to assess the efficiency of the control loops. The methodology allowing to calculate the risk is described. The results of the contour approach application to the technological process control at the Solntsevsky coal strip mine are presented.

Generalizing the Enhanced-Deep-Super-Resolution Neural Network to Brain MR Images: A Retrospective Study on the Cam-CAN Dataset.

The Enhanced-Deep-Super-Resolution (EDSR) model is a state-of-the-art convolutional neural network suitable for improving image spatial resolution. It was previously trained with general-purpose pictures and then, in this work, tested on biomedical magnetic resonance (MR) images, comparing the network outcomes with traditional up-sampling techniques. We explored possible changes in the model response when different MR sequences were analyzed. T1w and T2w MR brain images of 70 human healthy subjects (F:M, 40:30) from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) repository were down-sampled and then up-sampled using EDSR model and BiCubic (BC) interpolation. Several reference metrics were used to quantitatively assess the performance of up-sampling operations (RMSE, pSNR, SSIM, and HFEN). Two-dimensional and three-dimensional reconstructions were evaluated. Different brain tissues were analyzed individually. The EDSR model was superior to BC interpolation on the selected metrics, both for two- and three- dimensional reconstructions. The reference metrics showed higher quality of EDSR over BC reconstructions for all the analyzed images, with a significant difference of all the criteria in T1w images and of the perception-based SSIM and HFEN in T2w images. The analysis per tissue highlights differences in EDSR performance related to the gray-level values, showing a relative lack of outperformance in reconstructing hyperintense areas. The EDSR model, trained on general-purpose images, better reconstructs MR T1w and T2w images than BC, without any retraining or fine-tuning. These results highlight the excellent generalization ability of the network and lead to possible applications on other MR measurements.

THE PROBLEM OF REGULATING FUNGICIDES ON THE SKIN SURFACE FOR OCCUPATIONAL SKIN DISEASE IN AGRICULTURAL WORKERS’ RISK PREDICTION

The aim. To establish the norms of fungicides on the skin surface and predicting the risk of occupational skin pathology in agricultural workers to develop measures to prevent diseases caused by dermal exposure to pesticides. Materials and methods. The natural experiment was performed in accordance with modern requirements (European Food Safety Authority (2022), and the risk assessment was carried out according to the Recommendations (Approved by the Ministry of Health of Ukraine No. 324 issued on 13.05.2009) with different methods of spraying techniques: rod, air blast fan spraying, pre-sowing, aviation, knapsack treatment. 17 series of natural experiments were performed, and the air of the working zone area (n =56) and dermal exposure (n =56) were analyzed for each worker with different pesticide application methods. Quantitative determination of pesticide content was carried out by gas-liquid and high-performance liquid chromatography methods. The results were statistically processed using a package of licensed statistical programs MedStat v.5.2 (Copyright © 2003-2019) and Microsoft® Excel® for Microsoft 365 MSO. Results. It was established that there is pesticide contamination, mainly of the gloves of tank filling operators when preparing working solutions. No contamination of the skin surface was detected; only pesticide residues were present on the surface of the workers’ overalls. A comparison of the exposure dose in case of percutaneous exposure during the performance of technological operations with different methods of processing, dermal equivalents of Acceptable Operator Exposure Level of pesticide to workers’ skin (DE AOEL) and the allowable dermal dose for professional contingents (ADderm) and the hazard coefficients by dermal exposure (HCderm) showed that that dermal exposure during individual technological operations with different processing methods had a reliable difference between processing methods, but there is no difference within one application method. Conclusions. During the comparison of the hazard coefficients for dermal exposure, calculated according to different models, no significant difference was found between the risks calculated according to DE AOEL and ADderm for individual technological operations in various treatment methods, except for the operator who performed knapsack treatment and the risk calculated according to ADderm is significantly lower compared to the DE AOEL risk.

Multi-objective optimization strategy for regional multi-energy systems integrated with medium-high temperature solar thermal technology

The high proportion and volatility of renewable energy pose a significant challenge to efficient collaboration between photovoltaic/thermal and wind power in multi-energy systems. Therefore, this paper proposes a Regional Multi-Energy System (RMES) based on Medium-High Temperature Solar Thermal (MHTST) technology. The novelty of the solution integrates dispatchable photovoltaic and photothermal conversion pathways, facilitating flexible and controllable utilization of solar energy via installed Thermal Energy Storage (TES). A multi-objective optimization model is developed to ensure the optimal operation of the proposed system under typical seasonal scenarios. The method that combines Branch-and-Reduce with Multi-Learning-Task is used to handle the formulated Mixed Integer Nonlinear Programming (MINLP) and swiftly identify optimal Pareto solutions. Case studies are performed over the improved united communities of the Test Region for Energy Transition and Comprehensive Reform in Taiyuan, China. Compared with the conventional photovoltaic technology, the simulation results show that the proposed solution has superior performance in both winter-heating and summer-cooling operations across 24-hour scheduling periods: operating costs reduced by 12.5% and 18.7%, carbon emissions decreased by 7.4% and 21.4%, with local solar power accommodation increased by 263.89kW and 487.47kW, respectively.

Barriers and Challenges of Sustainable Logistics in Automobile Industry

Study Background and Objectives The automobile industry is a significant contributor to global environmental concerns. Vehicle production, transportation, and end-of-life management all have substantial environmental footprints. Sustainable logistics practices offer a path towards a greener future for industry. However, implementing these practices faces numerous challenges. This study aims to investigate the barriers and challenges hindering the adoption of sustainable logistics practices within the automobile industry. The specific objectives are: · To identify the key barriers faced by automobile manufacturers and their logistics partners in implementing sustainable practices. · To analyse the impact of these barriers on the environmental performance of the industry's logistics operations. · To develop recommendations for overcoming these barriers and promoting sustainable logistics practices within the automobile sector. Research Design This study employs a literature review methodology to analyze existing research on the barriers and challenges of sustainable logistics in the automobile industry. Relevant academic journals, conference proceedings, and industry reports are reviewed to identify key themes and insights. · Conduct a systematic and comprehensive review of relevant academic journals, industry reports, and government publications. · Utilize appropriate search engines and databases to identify relevant literature. · Analyse the collected data to identify key themes, trends, and research gaps. · Synthesize the findings to provide a comprehensive understanding of the barriers and challenges of sustainable logistics in the automobile industry. Major Findings The study reveals a growing consumer interest in the auto industry's commitment to sustainability. While price, performance, and safety remain significant purchase factors, a significant portion of consumers consider a car manufacturer's environmental practices when deciding. However, a knowledge gap exists, with many consumers lacking awareness of the environmental impact of traditional logistics practices. The research also highlights the importance of collaboration between car manufacturers, logistics companies, and policymakers in achieving significant progress towards sustainable practices. Standardized sustainability metrics and government incentives are seen as crucial factors for long-term success.

Enhancing high-speed CNC milling performance of Ti6Al4V alloy through the application of ZnO-Ag hybrid nanofluids

Abstract This research investigates the performance of high-speed CNC milling operations on Ti6Al4V alloy by employing a novel ZnO-Ag hybrid nanofluid. The study involves the preparation and characterization of nanofluids with varying concentrations of nanoparticles, focusing on thermal conductivity and stability. The machining experiments encompass four critical input parameters: Minimum Quantity Lubrication (MQL) flow rate, cutting speed, nanofluid concentration, and feed rate. Performance evaluation is based on average surface roughness (Ra) and cutting temperature. Key findings include a remarkable 21.05% improvement in thermal conductivity for the ZnO-Ag-based sunflower oil at 0.2% volume concentration compared to 0.05% concentration. The prepared nanofluids exhibit good stability. Moreover, cutting speed and MQL flow rate emerge as significant contributors to Ra, accounting for 35.62% and 34.82%, respectively. Interestingly, MQL flow rate is identified as the most influential factor, surpassing even cutting speed. SEM images for tool wear reveals that the ZnO-Ag based sunflower oil reduced tool wear significantly. In conclusion, the proposed ZnO-Ag-based sunflower oil at 0.2% concentration emerges as the good option for sustainable high-speed machining of Ti6Al4V alloy, showcasing

Sensitivity, linearity, and noise evaluation of L‐shaped dielectrically modulated label free tunnel field‐effect transistor biosensor

AbstractThis research article examines a L‐shaped dielectrically modulated label free TFET (L‐DM‐TFET) biosensor for the purpose of detecting different biomolecules using a label‐free biosensing detection technique. The proposed structure allows for the recognition of biomolecules by modulating various electrical properties, such as the drain current, transconductance, and linearity parameters. The source region of the proposed TFET incorporates a SiGe (source)/Si (channel) heterojunction, utilizing a low bandgap material of SiGe. This heterojunction is employed to enhance the ON‐state current of the devices. The materials used and the fabrication steps involved in our proposed device are compatible with complementary metal‐oxide‐semiconductor (CMOS) technology. This analysis is conducted using a calibrated Silvaco technology computer‐aided design (TCAD) simulator. Additionally, by considering a dielectric constant range of 1–12, we calculate various figure of merits (FOMs) parameters for the device. These include evaluation of linearity, sensitivity, and noise characteristics. Furthermore, we have conducted an analysis of linearity FOMs, such as VIP2, VIP3, IIP3, and IMD3 for the proposed device under study. Additionally, the linearity analysis of the presented tunneling FET (TFET) indicates the device's excellent performance in distortionless switching operations. Consequently, the L‐shaped dielectrically modulated biosensor holds potential suitability for high‐speed circuit designs.

Laparoscopic vs robotic inguinal hernia repair: a comparison of learning curves and skill transference in general surgery residents.

There is no consensus on whether laparoscopic experience should be a prerequisite for robotic training. Further, there is limited information on skill transference between laparoscopic and robotic techniques. This study focused on the general surgery residents' learning curve and skill transference within the twominimally invasive platforms. General surgery residents were observed during the performance of laparoscopic and robotic inguinal hernia repairs. The recorded data included objective measures (operative time, resident participation indicated by percent active time on console or laparoscopy relative to total case time, number of handoffs between the resident and attending), and subjective evaluations (preceptor and trainee assessments of operative performance) while controlling for case complexity, patient comorbidities, and residents' prior operative experience. Wilcoxon two-sample tests and Pearson Correlation coefficients were used for analysis. Twenty laparoscopic and forty-four robotic cases were observed. Mean operative times were 90min for robotic and 95min for laparoscopic cases (P = 0.4590). Residents' active participation time was 66% on the robotic platform and 37% for laparoscopic (P = < 0.0001). On average, hand-offs occurred 9.7 times during robotic cases and 6.3 times during laparoscopic cases (P = 0.0131). The mean number of cases per resident was 5.86 robotic and 1.67 laparoscopic (P = 0.0312). For robotic cases, there was a strong correlation between percent active resident participation and their prior robotic experience (r = 0.78) while there was a weaker correlation with prior laparoscopic experience (r = 0.47). On the other hand, prior robotic experience had minimal correlation with the percent active resident participation in laparoscopic cases (r = 0.12) and a weak correlation with prior laparoscopic experience (r = 0.37). The robotic platform may be a more effective teaching tool with a higher degree of entrustability indicated by the higher mean resident participation. We observed a greater degree of skill transference from laparoscopy to the robot, indicated by a higher degree of correlation between the resident's prior laparoscopic experience and the percent console time in robotic cases. There was minimal correlation between residents' prior robotic experience and their participation in laparoscopic cases. Our findings suggest that the learning curve for the robot may be shorter as prior robotic experience had a much stronger association with future robotic performance compared to the association observed in laparoscopy.

Sustainable vehicle allocation decisions under a vertical logistics collaboration setting

Enhancing vehicle utilization through a collaborative logistics approach allows businesses to contribute to the three pillars of sustainability by reducing fuel consumption and emissions, enhancing profit margins, and increasing customer satisfaction. This paper aims to introduce an Integer Linear Programming model for solving a vehicle allocation problem within a proposed vertical logistics collaboration setting. In this collaboration setup, production capacity allocation decisions are jointly made by collaborating customers and the logistics service provider, in order to create a more balanced and profitable logistics plan for all involved parties. Through the application of the proposed mathematical model, our numerical analyses illustrate the effects of the vertical logistics collaboration on the performance of transportation operations, including improved vehicle utilization rate and increased satisfied demand amount. Besides, we analyze the outputs of this operation related to the economic (by focusing on profit growth), environmental (by measuring the reduction in emissions), and social (by assessing the discounted transportation costs for customers) aspects of sustainability. To the best of our knowledge, no current study in the literature has established the vehicle allocation problem in the context of vertical logistics collaboration across all three sustainability pillars at the same time. The model can also serve as a tool for evaluating the potential economic, environmental, and social benefits arising from vertical collaboration and joint projects with customers, along with the support offered to logistics decisions.

Crowd Evacuation Management with Optimal Time‐Multiplexed Exit‐Choice Recommendations through Simulation Optimization

AbstractExit‐choice behavior significantly influences the performance of egress operations in crowded spaces. Thus, strategically issuing active exit‐choice recommendations that provide clear and concise guidance to pedestrians can help improve evacuation safety and efficiency. This study investigates how to optimally regulate pedestrian density at the exits by generating time‐multiplexed exit‐choice recommendations. The study develops a simulated crowd evacuation scenario with multiple exits, where pedestrians receive periodic sequences of exit‐choice instructions. The optimal period for each instruction is obtained through simulation‐optimization processes with three minimization objectives: evacuation time, cumulative density, and cumulative density variance. First, the effect of collective behaviors on evacuation performance is studied, which justifies the need for active mechanisms to improve exit‐choice decision‐making coordination. Then, several optimal plans for the different objectives are obtained and evaluated regarding evacuation time and cumulative density performance. Finally, the influence of adoption rate and collective commitment to instructions are evaluated. This study suggests that static plans, defined as time‐multiplexed exit‐choice instructions obtained through simulation‐optimization, reasonably represent a first step in the real deployment of intelligent crowd management systems.

Enhancing Team Performance in Surgical Operations: A Case Study at a Private Cancer Hospital and Research Centre in Thrissur District

Purpose: The purpose of this study is to evaluate the existing team dynamics within the surgical crew; to gain insights into the perceptions of different team members regarding team effectiveness and potential areas for improvement; to investigate factors crucial to successful teamwork in the operation theatre, and to analyze successful practices that have positively impacted team performance and patient outcomes. Design/methodology/approach: Quantitative data was gathered through a validated questionnaire distributed among surgical team members at a private cancer hospital and research center in Thrissur District, Kerala. Descriptive research was adapted for this study. The population for the study includes the members of the surgical team. A sample size of 120 members including doctors, nurses, technicians, and other supportive members who participated in various surgeries, were selected using a random sampling technique for the data purpose. Findings: The findings of the study disclosed that the challenges included occasional communication breakdowns and role ambiguity that seriously influenced the team performance of a surgical crew. Successful practices involved structured communication protocols, regular team training, and a collaborative leadership approach. Stakeholders accentuated the need for continuous improvement in strategies premeditated to the operation theatre’s unique demands. Research limitations/implications: The study’s inferences underscore the necessity for targeted intermediations focusing on the factors manipulating the surgical teams. Implementing structured training programs, refining communication protocols, and fostering a collaborative leadership culture can notably improve team performance. Additionally, modifying these interventions to suit the specific demands of the operation theatre is essential for sustaining and augmenting positive changes in teamwork dynamics, ultimately elevating the quality of patient care and outcomes. Social Implications: The empirical research contributed to enhancing the quality of surgical care, improving patient safety, and refining the overall performance of surgical teams in specialized healthcare settings through enhanced team performance for societal well-being by improving patient outcomes and reducing healthcare disparities. A more cohesive surgical team fosters a safer environment, positively impacting patient satisfaction, trust in healthcare, and overall community health. Additionally, it promotes a culture of collaboration and excellence, setting a precedent for improved healthcare practices within society. Originality / Value: The originality of the study lies in its broad examination of team dynamics within a specialized setting, the operation theatre of a private cancer hospital, and a research center. The study offers insights into specific challenges, successful practices, and context-specific interventions, to enhance team performance and patient care in this distinct healthcare environment.

Fourth industrial (r)evolution? Investigating the use of technology bundles and performance implications

PurposeThe purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.Design/methodology/approachUsing a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.FindingsOur findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.Originality/valueRelying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

Exploring the intra-platoon planning problem for heterogeneous train traffic under virtual coupling in the railway network via simulation

Study on the platoon planning of virtual coupling (VC) is indispensable for both passenger and freight railway operation in terms of capacity, scheduling, and timetabling. As an advanced technology in train operation and control systems, VC can significantly improve the performance of rail operations, with regards to capacity, flexibility and robustness. In this study, we mainly focus on the former one, i.e., to maximize the capacity gains, by employing the relative braking distance based spacing policy for heterogenous train traffic. To our knowledge, this article is the first to address the VC intra-platoon planning problem for a railway network. The main function/purpose of this study is to decide a leader train and allocate an order to the heterogeneous follower trains for the virtually coupled platoon in the off-line mode. The objective is transformed to minimize and compare the sum of minimum safe distance for platoons on the common shared route sections in the railway network from various perspectives, so as to seek the desirable orders of potential train consists within the platoons from the perspective of the whole railway network. Our contributions are mainly threefold. First, the conditions for train platooning under virtual coupling are synthesized. Second, the solution flow charts and algorithms for simulation are proposed, including general framework for simulation, classification of prioritizing the shared common route section, and flow charts and algorithms for decision of coupling order to train platoons. Finally, the proposed methodology was tested and discussed on the designed computational experiment (i.e., numerical simulations of a typical case study with two sets of test examples) via NetLogo platform. The numerical simulation results series revealed some key findings and validated the effectiveness of the proposed methodology. Results of this study can provide guidance to decision makers in timetabling and potential capacity bottleneck identification under VC. We believe that it is worth investigating and further advancing this research direction in the future.

Dynamic Performance of Liquid Smooth Annular Seal Operating in the Transition Regime

Abstract This paper presents the experimental leakage and rotordynamic performance for a liquid smooth annular seal operating in the transition regime. The test conditions include pressure differentials up to 64 bars with 1∼2 bar increments for 6 rotor speeds (2.5, 3.8, 5, 7.5, 8.8, and 10 krpm), as well as nonrotating rotor case under zero preswirl condition. The rotordynamic coefficients for all the test conditions are obtained by pseudo-random excitation of the seal at multiple subsynchronous frequencies. By considering the transition Reynolds number (1000 &amp;lt; Re &amp;lt; 3000) and the Taylor Number (Ta) versus Axial Reynolds Number (Rez), the variations in the direct stiffness coefficients (K) can used as an indicator of the flow regime transition boundaries. The direct stiffness K resulting from the Lomakin and hydrodynamic effects significantly drops until Rez reaches ∼1500. For higher Rez, K increases mainly due to hydrodynamic effects. When K drops, the cross-coupled stiffness k, the direct damping C and the cross-coupled virtual mass m increase while the cross-coupled damping c and virtual mass M decrease. None of predictions based on either laminar or turbulent flow show the variations in rotordynamic coefficients obtained from experimental results. The leakage is not highly influenced by rotor speeds for low speed cases crossing laminar boundary as ΔP increases, however, results for higher speeds in the superlaminar region show reduced leakage rates as rotor speed increases.

Harnessing nonlinear conductive characteristic of TiO2/HfO2 memristor crossbar for implementing parallel vector–matrix multiplication

Memristor crossbar arrays are expected to achieve highly energy-efficient neuromorphic computing via implementing parallel vector–matrix multiplication (VMM) in situ. The similarities between memristors and neural synapses offer opportunities for realizing hardware-based brain-inspired computing, such as spike neural networks. However, the nonlinear I–V characteristics of the memristors limit the implementation of parallel VMM on passive memristor crossbar arrays. In our work, we propose to utilize differential conductance as a synaptic weight to implement linear VMM operations on a passive memristor array in parallel. We fabricated a TiO2/HfO2 memristor crossbar array, in which differential-conductance-based synaptic weight exhibits plasticity, nonvolatility, multi-states, and tunable ON/OFF ratio. The noise-dependent accuracy performance of VMM operations based on the proposed approach was evaluated, offering an optimization guideline. Furthermore, we demonstrated a spike neural network circuit capable of processing small spiking signals through the differential-conductance-based synapses. The experimental results showcase effective space-coded and time-coded spike pattern recognition. Importantly, our work opens up new possibilities for the development of passive memristor arrays, leading to increased energy and area efficiency in brain-inspired chips.