Cycle Counting Research Articles

Modeling nonlinear stress-strain model for sulfate dry-wet cycle erosion of concrete: considerations for the initial compaction stage

Sulfate dry-wet cycle erosion significantly affects the mechanical properties of concrete. Investigating the uniaxial compressive stress-strain relationship under these conditions is essential for developing accurate constitutive models. This study analyzes the uniaxial stress-strain curves of concrete subjected to dry-wet cycles in 5% and 15% sulfate solutions. The results show that the initial compaction phase in the stress-strain relationship is particularly pronounced under increasing sulfate concentrations and cycle counts. The concrete experiences an extended compaction phase, which accounts for up to 35.71% of the total strain process. This finding challenge traditional constitutive models, which struggle to accurately describe this phase. To address this issue, the study develops a nonlinear stress-strain model for concrete, incorporating the initial damage caused by sulfate dry-wet cycle erosion, based on Weibull statistical damage mechanics principles. The research indicates that the effects of sulfate concentration and cycle count are predominantly reflected in the pronounced nonlinearity of the skeleton strain function’s opening size (a) and shape characteristics (b), modeled using a fourth-degree polynomial. The model demonstrates an excellent fit to experimental data with an R2 value of 0.99989, showing that the proposed nonlinear stress-strain relationship effectively captures the uniaxial mechanical behavior of concrete under sulfate dry-wet cycle erosion and provides a robust framework for developing constitutive models in such environments.

Approximation of subgraph counts in the uniform attachment model

Abstract We use Stein’s method to obtain distributional approximations of subgraph counts in the uniform attachment model or random directed acyclic graph; we provide also estimates of rates of convergence. In particular, we give uni- and multi-variate Poisson approximations to the counts of cycles and normal approximations to the counts of unicyclic subgraphs; we also give a partial result for the counts of trees. We further find a class of multicyclic graphs whose subgraph counts are a.s. bounded as $n\to \infty$ .

Measuring the impact of automated dispensing cabinets implementation on data and inventory management of human normal immunoglobulin in an acute teaching hospital: A pre- and post- intervention study

BackgroundHuman Normal Immunoglobulin (HNIg) is a complex plasma-derived blood product used to treat a variety of medical conditions. Global supply problems have increased focus on HNIg stewardship, including mandatory recording of HNIg usage on the National Immunoglobulin Database (NIgD). Local departmental audits identified significant inconsistencies in data uploaded to NIgD. Inventory management issues caused a number of stock losses in the last financial year. A paper-based HNIg batch number recording system was replaced with the use of Automated Dispensing Cabinets (ADCs), which generated an electronic batch number report, with matching fields required for electronic upload to NIgD. AimTo measure the impact of ADC implementation on the accuracy of data uploaded to NIgD, HNIg stock control and staff time associated with processes of HNIg data and inventory management. MethodThree months of pre- and post-implementation HNIg dispensing data was compared to the data uploaded to the NIgD for discrepancies. Inventory reports were used to identify unexplained stock adjustments. Time and motion methods were used to quantify staff time associated with HNIg activities. ResultsPre-implementation: 20.7 % (3762.5 g/18,217 g) of HNIg by volume (23.7 % of dispensing episodes; 66/279) were inaccurately uploaded or absent on the NIgD and three stock adjustments were made (loss of >£15 k). Post-implementation: 12 % (2325 g/19,347 g) of HNIg by volume (10.8 % of dispensing episodes; 31/286) were inaccurately uploaded or absent on the NIgD and zero stock adjustments were observed; Mean time for dispensing per HNIg prescription reduced from 17 min to 8 min; Time spent uploading data to NIgD per month reduced from 5 h to 1.75 h. Discussion/ConclusionThe use of ADCs improved accuracy of NIgD data upload. Following implementation direct observations have cited unregistered or finished patient episodes, dispensing procedural compliance, and user familiarity with the system as common reasons for incomplete data uploads to NIgD. The new ADC process had consequences of forcing dispensing procedure compliance to improve uploads, whilst reducing dispensing times. It led to improved stock control and removed upload burden from dispensers. ADC stock discrepancy alerts allowed staff to proactively resolve discrepancies in real time. Time taken for additional processes to support management of stocks in ADCs, including monthly stock cycle counts, were important considerations for implementation. The key advantage of using ADC batch number reports is the ability to upload as a single monthly batch without having to manually access individual patient records on the NIgD. It facilitates early identification of failed upload attempts and supports resolution of stock discrepancies.

Modeling the service life of temporary airfield operational surfaces under multi-pass aircraft trafficking

Expeditionary Airfield (EAF) surfacing systems are designed to create temporary aircraft operating surfaces. Modeling the service life of EAF surfacing systems including the matting system, aircraft, and subgrade, has historically proven difficult, exacerbated by variability between systems and the multitude of mechanisms that can constitute failure. The study presented herein outlines the development and implementation of a performance modeling approach that includes a multi-scale scheme that accounts for local characteristics of the connection points of the EAF matting system, coupled to the global characteristics of the matting array to predict cyclic passes to failure. Finite element studies were conducted for an EAF surfacing system brickwork configuration subjected to aircraft strut loads over varying California Bearing Ratio (CBR) subgrades to calibrate a transfer function to full-scale trafficking experiments. The proposed framework is then used to predict the rate of subgrade deformation for additional lay patterns, which successfully ranked the performance of each relative to full-scale trafficking experiments. An approach is proposed to couple the rate of subgrade deformation with local finite element models to capture increasing joint damage as permanent deformation accumulates, and supplemented by a variable amplitude cycle counting and damage accumulation algorithm that yields reasonable agreement with full-scale experiments while capturing the transition in failure mechanisms at higher CBR values. The results of the study presented herein captures the propensity for end connector and subgrade failure over a range of subgrade CBRs and shows promise for a broader performance framework that can be extended to other EAF surfacing systems, aircraft types, and specific matting lay patterns.

Power Semiconductor Junction Temperature and Lifetime Estimations: A Review

The lifetime of power electronic systems is the focus of both the academic and industrial worlds. Today, compact systems present high switching frequency and power dissipation density, causing high junction temperatures and strong thermal fluctuations that affect their performance and lifetime. This paper is a review of the existing techniques for the electro-thermal modelling of Mosfet and IGBT devices regarding lifetime estimation. The advantages and disadvantages of the methodologies used to achieve lifetime prediction are discussed, and their benefits are highlighted. All the factors required to predict power electronic device lifetime, including Mosfet and IGBT electrical models, the computation of power losses, thermal models, temperature measurement and management, lifetime models, mission profiles, cycle counting, and damage accumulation, are described and compared.

Demonstrative irregular fatigue cycle counting by rainflow method implementation using a Python program

Demonstrative irregular fatigue cycle counting by rainflow method implementation using a Python program

Prediction of fatigue life of a bolted joint in railway steel arch bridge using multiaxial fatigue criteria

Fatigue represents a critical condition for infrastructure subjected to repeated cyclic loads, such as steel railway bridges. The literature offers several methods to estimate fatigue life, consisting of three main phases: cycle counting, fatigue damage criterion, and damage accumulation criterion. Applying S-N curves might not be conservative in the case of railway bridges subjected to traffic because the stress-time history is complex and cannot be reduced to a sinusoidal history. Additionally, the presence of a multiaxial stress state must be considered. Therefore, this work compares eight multiaxial fatigue damage criteria for evaluating fatigue life in a scenario between high and low-cycle fatigue. Specifically, the authors considered four low-cycle fatigue criteria, namely Smith–Watson–Topper (SWT), Kandil, Brown and Miller (KBM), Glinka, Fatemi and Socie (FS), and four high-cycle fatigue criteria, Crossland, Basquin and the methods recommended by Eurocode 3 and British Standard. The rainflow counting method in ASTM E1049-85 (2011) and Miner’s rule for damage accumulation were used. The Polcevera railway steel bridge was selected as a case study. A 3D numerical model was developed for this purpose using Midas Civil software, taking into account the material non-linearity of the bridge’s elements. Once the area with the highest stress concentration was identified, a detailed analysis was conducted to estimate the stress and strain time histories induced by train traffic. A sensitivity analysis was conducted after critically comparing the eight methods for predicting fatigue life to assess the impact of traffic parameters, train velocity, axle load, and convoy length on fatigue life. It has been found that the criteria considering axial stress tend to overestimate the number of fatigue cycles to failure compared to the criteria, including the effect of shear stress components.

Recurrent neural networks as virtual cavity pressure and temperature sensors in high-pressure die casting

High-pressure die casting (HPDC) is a permanent mold-based production technology that facilitates the casting of near net shape components from nonferrous alloys. The pressure and temperature conditions within the cavity impact the cast product quality during and after the conclusion of the die filling process. Die surface cavity sensors can deliver information describing the conditions at the die-casting interface. They are associated with high costs and limited service lifetimes below the achievable total cycle count of the die inserts and therefore ill-suited for industrial use cases. In this work, the suitability of long short-term memory (LSTM) recurrent neural networks (RNN) for substituting physical cavity temperature and pressure sensors virtually after the production ramp-up or at the end of the sensor service life is investigated. Training LSTMs with data of 233 casting cycles with different process parameters provides networks which are then applied to 99 further cycles. The prediction accuracy is investigated for different time interval lengths in the solidification and cooling phase. For longer time intervals, the cavity pressure prediction deteriorates, potentially due to a highly individual and hardly ascertainable buildup of casting distortion and internal stresses. Overall, however, the accuracy of the developed LSTMs is excellent for the cavity temperatures and good for the cavity pressures.

Photocurable Foam for Three-Dimensional-Printed Porous Structures.

In this research, a foam three-dimensional (3D) printing method using digital light processing (DLP) technology was developed to fabricate 3D-printed porous structures. To address the challenges in preparing DLP precursor foam fluid, we designed a specialized foaming device. This device enables the precursor solution to be blended with air, resulting in a stable foam precursor with an adjustable air/liquid fraction and suitable fluidity, crucially enhancing the gas-liquid contact time for the printing process. By manipulation of fluid flow rates, cycle counts, and gas/liquid ratios, one can easily prepare uniform foams with precise control over the pore size and porosity. To avoid significant volume reduction during ultraviolet (UV) curing, nanoparticle fillers were introduced into the network to prevent collapse of the foam structure. Furthermore, the inclusion of an UV absorber enhanced the quality of the printing process by addressing the limitations associated with particle scattering and reflection. The DLP process can readily fabricate intricate structures, featuring a planar resolution below 30 μm and a printing accuracy of less than 1%. Several examples were also demonstrated to highlight the advantages of this technology and its ability to directly print custom foam structures, thereby saving time and material resources.

Enhancing Fatigue Resistance of Polylactic Acid through Natural Reinforcement in Material Extrusion.

This research paper aims to enhance the fatigue resistance of polylactic acid (PLA) in Material Extrusion (ME) by incorporating natural reinforcement, focusing on rotational bending fatigue. The study investigates the fatigue behavior of PLA in ME, using various natural fibers such as cellulose, coffee, and flax as potential reinforcements. It explores the optimization of printing parameters to address challenges like warping and shrinkage, which can affect dimensional accuracy and fatigue performance, particularly under the rotational bending conditions analyzed. Cellulose emerges as the most promising natural fiber reinforcement for PLA in ME, exhibiting superior resistance to warping and shrinkage. It also demonstrates minimal geometrical deviations, enabling the production of components with tighter dimensional tolerances. Additionally, the study highlights the significant influence of natural fiber reinforcement on the dimensional deviations and rotational fatigue behavior of printed components. The fatigue resistance of PLA was significantly improved with natural fiber reinforcements. Specifically, PLA reinforced with cellulose showed an increase in fatigue life, achieving up to 13.7 MPa stress at 70,000 cycles compared to unreinforced PLA. PLA with coffee and flax fibers also demonstrated enhanced performance, with stress values reaching 13.6 MPa and 13.5 MPa, respectively, at similar cycle counts. These results suggest that natural fiber reinforcements can effectively improve the fatigue resistance and dimensional stability of PLA components produced by ME. This paper contributes to the advancement of additive manufacturing by introducing natural fiber reinforcement as a sustainable solution to enhance PLA performance under rotational bending fatigue conditions. It offers insights into the comparative effectiveness of natural fibers and synthetic counterparts, particularly emphasizing the superior performance of cellulose.

Fatigue damage accumulation in a bolted joint subjected to the random loading

Fatigue damage in structures, which escalates with cyclic loading, is traditionally analyzed using blocks of constant amplitude. This study aims to derive the fatigue loading spectrum for the Cirrus SR20 multipurpose airplane and predict the fatigue life of its main spar connection. Using available reference loading data from acrobatic and training aircraft, the loading spectrum was established, and constant amplitude loading blocks were determined through the Rainflow cycle counting and statistical methods. Fatigue damage in the bolted joint was assessed using both linear and nonlinear Miner rules, revealing that results from nonlinear criteria tend to converge towards those from linear predictions as loading blocks increase. This approach provides a robust predictive framework for assessing the fatigue life of airplane components under variable amplitude loadings, potentially enhancing maintenance protocols and structural design durability.

Probabilistic hydrogen-assisted fatigue crack growth under random pressure fluctuations in pipeline steels

The increasing demand for energy and the global threat of climate change have driven the search for alternative energy sources, with hydrogen emerging as a prominent substitute for fossil fuels. The fatigue behavior of pipeline steels under gaseous hydrogen is a critical problem that is impeding the industry's adoption of hydrogen into the current natural gas infrastructure. A brief review of existing hydrogen-assisted fatigue crack growth (HA-FCG) studies, which reveal several key gaps, is given first. Existing HA-FCG models predominantly address constant amplitude loading, while the realistic driving force is random loading in gas pipelines. Also, the current uncertainty quantification studies for HA-FCG focus on material randomness and overlook the large uncertainties associated with random pressure fluctuations. To address these issues, this study proposes a HA-FCG model that utilizes a time-based subcycle approach, allowing for direct application to random spectrum loads without the need for cycle counting. A model parameter as a function of hydrogen operating conditions is introduced to capture the different regimes in HA-FCG, and the model predictions are compared with ASME B31.12 code. Following this, statistical analysis of random pressure fluctuation data collected from natural gas pipelines at multiple locations is performed. The realistic industry pressure data shows distinct statistical features, and it is observed that the high-fidelity data (high sampling frequency) is beneficial for accurate fatigue life predictions. Uncertainty quantification and load reconstruction are performed by the Karhunen–Loève expansion with a post-clipping procedure, leading to a probabilistic HA-FCG analysis. The paper concludes with key findings and suggests directions for future research.

Polyethylene Wear Testing of a Non-Mechanically Linked Total Elbow Replacement

The objective of this study was to perform a polyethylene wear test on a non-mechanically linked total elbow arthroplasty implant using a clinically relevant in-vitro elbow wear test methodology that simulated ten years of use in the light to moderate activity of daily living range. The test protocol applied an 80° arc of ulnohumeral motion beginning at 30° shy of full extension and progressing to 110° of flexion. Force was applied at 7° to recreate a valgus load on the elbow. A variable joint load profile at a frequency of 0.5 Hz was employed. The implants were tested for 5 million cycles (Mc) in a bovine serum lubricant. Implant component failure was characterized and polyethylene wear was determined gravimetrically. After 5 Mc the small polyethylene bushing wear rate was 0.56 mg/Mc. The medium size wear rate was 0.28 mg/Mc. Three large sizes were tested and the average wear rate was 0.39 ± 0.07 mg/Mc. No implant failure was identified. The test recreated an in vivo loading environment and measured polyethylene wear rates at specified cycle counts. The test demonstrated less wear than other joint replacements. Further clinical evaluation is necessary to determine if this translates into reduced complications of total elbow replacement associated with wear.

Topology optimization for fatigue reserve factors

This paper describes a topology optimization approach that applies the common fatigue analysis practices of rainflow cycle counting and critical plane searches to cover both proportional and non-proportional fatigue loading conditions of metals. The existing literature on topology optimization has so far mainly considered fatigue damage under proportional loading conditions and typically uses continuous damage models to avoid the discontinuous nature of fatigue rainflow cycle counting and critical plane searches. Furthermore, previous publications often introduced heuristic schemes to scale the fatigue damage and set the move limits for the design variables rather low to avoid oscillations in the design variables and damage responses during the optimization iterations, because fatigue damage is typically highly localized. Therefore, these approaches cause many optimization iterations. Contrarily, our present approach applies the fatigue reserve factor (FRF) directly in the optimization formulation instead of the fatigue damage where FRF is a fatigue reserve factor for infinite fatigue life. The inverse FRF scales nearly linearly with the stresses. Therefore, the present approach needs no heuristic scaling for the fatigue topology optimization. The numerical implementation applies the semi-analytic adjoint sensitivity method for multiple load cases. Numerically, FRF shows more stable optimization convergence using less optimization iterations. Different FRF topology-optimized designs for a variety of fatigue damage types are validated and compared. Additionally, the optimized FRF designs are compared to both strictly stiffness optimized designs and stress strength optimized designs.

Energy efficient and low-latency spiking neural networks on embedded microcontrollers through spiking activity tuning

In this work, we target the efficient implementation of spiking neural networks (SNNs) for low-power and low-latency applications. In particular, we propose a methodology for tuning SNN spiking activity with the objective of reducing computation cycles and energy consumption. We performed an analysis to devise key hyper-parameters, and then we show the results of tuning such parameters to obtain a low-latency and low-energy embedded LSNN (eLSNN) implementation. We demonstrate that it is possible to adapt the firing rate so that the samples belonging to the most frequent class are processed with less spikes. We implemented the eLSNN on a microcontroller-based sensor node and we evaluated its performance and energy consumption using a structural health monitoring application processing a stream of vibrations for damage detection (i.e. binary classification). We obtained a cycle count reduction of 25% and an energy reduction of 22% with respect to a baseline implementation. We also demonstrate that our methodology is applicable to a multi-class scenario, showing that we can reduce spiking activity between 68 and 85% at iso-accuracy.

Analysis of Inventory Management System at Pharmacy of XYZ Hospital

This research examines inventory management at the XYZ Hospital Pharmacy Installation in Bandung, with a special focus on medicines and medical devices. The background to this research is the significant increase in health costs and the importance of effective supply chain management to reduce unnecessary costs. Based on monthly stock and daily sales data from October 2023 to February 2024, this research uses quantitative methods to calculate optimal inventory levels, including Economic Order Quantity (EOQ), safety stock, and reorder point (ROP). This research also applies ABC analysis and cycle counting to prioritize inventory control. The research results show that the proposed inventory policy, especially the continuous review strategy, has the potential for significant cost savings for the XYZ Hospital Pharmacy Installation. For pharmaceutical products, achieving a 99% service level can result in savings of IDR 302,697,429, which is 48.17% of the average inventory level. For medical devices, potential savings reach IDR 70,602,064, which is 48.77% of the average inventory level. The total potential savings for all products is IDR 373,299,493. These findings highlight that hospitals currently do not have effective controls in managing inventory of single-use medical devices. Implementing strong inventory policies and procedures is critical to improving cost efficiency and optimizing inventory levels within an organization.

Effect of MWCNTs on static, dynamic, and wear performance of Vacuum Assisted Resin Infusion Molding (VARIM) processed glass fabric/epoxy polymer composites

In the present work, MWCNTs were used in wt.% of 0.075, 0.15, and 0.3 in epoxy resin, and then glass fabric/epoxy polymer (GF/EP) composites were fabricated using VARIM setup. The mechanical and wear properties of GF/EP composites were compared with and without the addition of MWCNTs. Maximum improvement in tensile and flexural performance were seen in GF/EP composites at 0.15 weight percent MWCNT addition when compared to a neat GF/EP one, based on static testing such as tensile and flexural tests. High-cycle fatigue test results show a relatively higher cycle count with 0.15 wt.% MWCNTs addition in the GF/EP composite compared to the GF/EP without the addition of MWCNTs. The wear performance also improved with a lower friction coefficient as well as a lower track depth and width for MWCNTs with added GF/EP than plain GF/EP composite. Therefore, in addition to decreasing surface softening and improving the wear performance of glass fabric epoxy composites, MWCNTs (0.15 weight percent) increased the interfacial adhesion at the fiber/matrix interface. This study establishes an optimum ratio of 0.15 wt.% of MWCNTs addition in glass fabric/epoxy polymer composites for enhancement in their mechanical and wear performance.

Heliostat Fatigue Loads

An approach to estimate the wind load spectra for heliostats is proposed. It is based on the wind-induced fatigue cycle counts for buildings given by the Eurocode EN 1991 and considers heliostat specific impact factors. The approach can be further refined if data on specific wind and heliostat field properties are available.

Tackling inventory losses of small accessories in engineering manufacturing: a case study of Euro Manufacturing

Learning outcomes After completion of the case study, the students will be able to understand ABC analysis and develop a systematic approach using PDCA, analyze processes, technology, employee training and supplier relationships when analyzing shrink and developing solutions, evaluate how technology improves production inventory control and visibility and recognize the importance of fostering a culture of employee accountability and ownership to minimize inventory loss and improve overall operational efficiency. Case overview/synopsis On June 2, 2023, sitting in his office in Karachi, Pakistan, Khan Aamir, the manager of store and inventory at Euro Manufacturing, found himself immersed in a cloud of confusion. The incessant loss of inventory items, particularly the nut bolts and small accessories, had become a perplexing challenge. To address these losses and provide a cycle count report to the director of supply chain, Aamir, manager of store and inventory, was given the responsibility to take action. He was looking for a comprehensive approach to address the current problems and prevent further losses in the future. This case study examines the various reasons for the losses, including theft, inadequate inventory control methods, human error and problems with suppliers. It highlights the importance of established procedures, the use of technology (such as barcode scanning, radio-frequency identification tagging and inventory management software) and the cultivation of a culture of accountability among employees. Complexity academic level This case study is developed for class discussion in the course of operations management or supply chain management. This case study is suitable for use with undergrad students. This case study can be taught in a module on operations management or supply chain management, as part of a broader course in business management or industrial engineering. Supplementary materials Teaching notes are available for educators only. Subject code CSS: 9: Operations and logistics.

Mode-{I, III} multiaxial fatigue of welded joints in steel maritime structures: Total stress based resistance incorporating strength and mechanism contributions

Arc-welded joints in steel maritime structures are typically identified as weakest links in terms of fatigue limit state performance. Multiaxiality can be involved, consisting of predominant mode-I and non-negligible mode-III components. Aiming to answer the question if a cracked geometry based fatigue strength parameter would outperform an intact geometry based one like the effective notch stress, the total stress is adopted. A von Mises type of criterion is defined at the critical fracture plane and includes mode specific and material characteristic strength and mechanism contributions. A lifetime dependent shear strength coefficient is introduced to cover the resistance curves intercepts and slopes, whereas the total stress parameter contains the mean stress contribution as well as the (mixed) mode dependent notch and crack tip elastoplasticity coefficients, reflecting an interaction mechanism. Cycle counting includes a cycle-by-cycle non-proportionality measure and damage accumulation is based on a linear model. Evaluating mid-cycle fatigue resistance data, the total stress and effective notch stress performance turns out to be similar. However, the total stress related elastoplasticity coefficients are an explicit and sensitive measure to incorporate the actual physics of the fatigue damage process, whereas the material characteristic lengths for the effective notch stress seem to be more implicit and less sensitive ones.