•New efficient methods are presented to classify failure modes in RC columns.•Machine learning techniques were utilized to predict the failure modes.•The comparison study shows the desired accuracy ...of the proposed model.•The proposed techniques could specify the failure mode without a complex calculation.•The models have many applications in structural engineering.
In this article, new efficient methods are presented to classify failure modes in reinforced concrete columns. For this purpose, machine learning techniques were utilized with consideration of laboratory datasets collected from the literature. Two different approaches, including decision tree and artificial neural network, have been studied to determine the failure mode of the columns. The variables used to estimate the failure mode were compressive strength of the concrete, span-to-depth ratio, axial load ratio, longitudinal reinforcement ratio, volumetric transverse reinforcement ratio, yield stress of longitudinal reinforcement, and yield stress of transverse reinforcement. A comparison study between the two introduced models indicated that the proposed decision tree provides a desirable accuracy and could specify the failure mode, with no need to a complex calculation. The proposed model has many applications in structural engineering such as seismic evaluation, retrofitting, and rehabilitation as a suitable tool for estimating the failure modes in reinforced concrete columns.
Peak shear strength estimation of RC shear walls is one of the influential parameters on the design of RC shear walls. Considering all models and equations provided by researchers and building design ...codes, it is still not possible to estimate the peak shear strength of shear walls with high level of accuracy. Therefore, the authors proposed three innovative models to estimate the peak shear strength based on combination of the Support Vector Regression with meta-heuristic optimization algorithms such as Teaching–learning-based optimization (TLBO), Particle swarm optimization (PSO), and Harris Hawks Optimization (HHO). The authors collected a large database containing 228 experimental data of RC shear walls and eight input parameters. One of the best features of this research is providing models for prediction of shear strength for three categories including, squat, cylinder, and thin RC shear walls.
Finally, all three models have been compared with each other and with the equations proposed by the design codes and the researchers. The results indicate that the proposed models have good accuracy. As a result, researchers can use these models to estimate the shear strength of RC shear walls, which could increase the accuracy in predicting the behavior of the structure and would reduce the construction costs.
•Three innovative models to estimate the peak shear strength are proposed.•A large database containing 228 experimental data of RC shear walls were collected.•All categories of RC walls including squat, cylinder, and thin ones were considered.•The proposed models could increase the accuracy in predicting the behavior of the structures.
Reinforced concrete (RC) shear walls play a pivotal role in resisting seismic and lateral loads within structural frameworks. A thorough examination of the existing literature was undertaken, ...covering a range of experimental and theoretical studies related to the design of RC shear walls. It was emphasized that comprehending shear failure behavior and precisely predicting the shear strength of RC walls holds considerable significance. To address this, the study proposes two models that integrate the support vector regression method with meta-heuristic optimization algorithms (Bat and GOA), utilizing 228 sets of experimental data. In identifying the parameters influencing the shear strength of RC shear walls, the study focused on eight influential factors. The comparison of the two proposed models in the current research with existing models and experimental data demonstrated their commendable accuracy, surpassing the performance of suggested empirical formulations. The prediction errors associated with the proposed models, when compared to experimental data, were notably low. An innovative approach was introduced in the research, presenting a novel method for predicting shear strength using the support vector regression method and the Bat optimization algorithm. A notable advantage of this formulation lies in its capacity to predict the shear strength across various configurations, including squat, cylindrical, and thin RC shear walls. Unlike some existing equations for predicting shear strength, this formulation exhibits no limitations. Through a comparative analysis with established equations, the computational framework’s results suggest its successful applicability in building codes and construction practices. The proposed method contributes to the accurate prediction of shear strength in diverse RC shear wall configurations, offering a valuable tool for structural engineering applications.
This paper develops a data-driven model that quantifies the benefits of supply chain collaboration initiatives such as a continuous replenishment program (CRP). CRP is a well-established supply chain ...collaboration program that is widely used in business. The model computes the cost savings of CRP for both partners involving inventory holding, transportation and ordering/handling cost components. The savings drivers associated with each cost component are identified and used to quantify the impact of CRP. The model is applied in a healthcare supply chain case study where a manufacturer seeks to estimate the cost savings of a business relationship with a distributor. The results indicate that CRP reduces the total cost of the supply chain by 19.1%. In this instance, the distributor gains disproportionately more savings in the shared cost components. The variability and sensitivity of cost savings across the network reveal the supply chain parameters that affect the partner savings.
In the two past decades, ferrocement members have been with a wide variety of uses in structural applications because of their unique physical properties (high surface-area-to-volume ratio and ...possible fabrication in any shape). In this study, two models were presented for a predict of the moment capacity of ferrocement members, one based on a back-propagation multilayer perceptron artificial neural network and the other proposing a new equation based on the multilayer perceptron network trained. These models with five input parameters including volume fraction of wire mesh, tensile strength, cube compressive strength of mortar, and width and the depth of specimens are presented. The results obtained from the two models are compared with experimental data and experimental equations such as plastic analysis, mechanism, and nonlinear regression approaches. Also, these results are compared with the results of the equations that researchers have proposed in recent years with soft computing methods (ANFIS, GEP, or GMDH). The prediction performance of the two models is significantly better than the experimental equations. These models are comparable to that of models provided with different soft computing methods to predict the moment capacity of ferrocement members. The result of this research has proposed a general equation with less mathematical complexity and more explicit.
Background: Drug abuse is one of the major socio-medical problems of our time with a global scope. Abusing street drugs is on the rise among adults and is considered as a public health concern. In ...addition, limited studies are available in this regard. The aim of this study was to investigate the frequency of street drug poisoning in the Razi Hospital of Ahvaz in Iran during 2008-2013.
Methods: This is an epidemiological cross-sectional study based on hospital information. All admitted cases with street drug poisoning were included during 2008 to 2013 (70 patients). Data were analyzed by SPSS software using descriptive statistics and Chi-square.
Results: In the current study, out of 70 cases aged 13-53 years old, the highest frequency of abusers was related to 30 years of age, and male/female ratio was 4 to 1. Among the drugs used, methamphetamine accounted for the highest rate. In this study, 55.7% of the cases needed to be admitted to the intensive care unit and 2 deaths were observed. The most common symptom among poisoned patients includes loss of consciousness and the least common symptom is respiratory distress.
Conclusion: According to the results, it can be concluded that the poisoning will be rarely fatal in case of dangerous exposure, if they are under supervision of emergency medical attentions, including the careful management of airways and respiratory failure, hypotension monitoring, seizure and impaired management of body temperature.
Supply chain collaboration programs, such as continuous replenishment program (CRP), is among the most popular supply chain management practices. CRP is an arrangement between two partners in a ...supply chain to share information on a regular basis for lowering logistics costs while maintaining or increasing service levels. CRP shifts the replenishment responsibility to the upstream partner to avoid the bullwhip effect across the supply chain. This dissertation aims to quantify, measure, and expand the benefits of CRP for the purpose of reducing logistics cost and improving customer service. The developed models in this dissertation are all applied in different case studies supported by a group of major healthcare partners. The first research contribution, discussed in chapter 2, is a comprehensive data-driven cost approximation model that quantifies the benefits of CRP for both partners under three cost components of inventory holding, transportation and ordering processing without imposing assumptions that normally do not hold in practice. The second contribution, discussed in chapter 3, is development of a verifiable efficiency measurement system to ensure the benefits of CRP for all partners. Multi-functional efficiency metrics are designed to capture the trade-off in gaining efficiency between multiple functions of logistics (i.e. inventory efficiency, transportation efficiency, and order processing efficiency). In addition, a statistical process control (SPC) system is developed to monitor the metrics over time. We discuss suitable SPC systems for various time series behaviors of the metrics. The third contribution of the dissertation, discussed in chapter 4, is development of a multi-objective decision analysis (MODA) model for multi-stop truckload (MSTL) planning. MSTL is becoming increasing popular among shippers while is experiencing significant resistance from carriers. MSTL is capable of reducing the shipping cost of shippers substantially but it can also disrupt carriers’ operations. A MODA model is developed for this problem to incorporate the key decision criteria of both sides for identifying the most desirable multi-stop routes from the perspective both decision makers.
•Recent developments in the production and applications of biochar have been summarized.•Conversion techniques of biochar have been described.•Biochar properties and its environmental benefits are ...assessed.•Impact of biochar on soil fertility is presented.
Lignocellulosic biomass has attracted an extraordinary amount of attention because of its high availability and low price as one of the sustainable and renewable resources for producing valuable products, such as biochar. This study reviews latest research on biochar production through the pyrolysis process and its applications. Technologies based on pyrolysis, such as mild & fast pyrolysis, gasification, are promising strategies for converting lignocellulosic biomass to materials with high added value (biochar, bio-oil, biogas, etc.). Biochar is capable of controlling climate fluctuations through carbon sequestration. Another unique feature of this material is its ability to increase soil fertility, improve soil, and increase agricultural yield; therefore, soils have the best fertility in areas where biochar is present. The use of pyrolysis (under controlled and optimal conditions) can produce quality biochar that finds numerous applications in various fields. According to the research conducted on biochar production processes, the highest percentage of biochar with a percentage above 35 is related to the torrefaction process and after that pyrolysis and gasification with approximate percentages of 12–34 and 10%, respectively.
Rare and extreme climate events may result in wide power outages or blackouts. The concept of power system resilience has been introduced for focusing on high-impact and low-probability (HILP) events ...such as a hurricane, heavy snow, and floods. Power system resilience is the ability of a system to reduce the likelihood of blackout or wide power outages due to HILP events. Indeed, in a resilient power system, as the severity of HILP events increases, the rate (but not the amount) of unserved loads diminishes. Suitable measures for managing power system resilience can be classified into three categories in terms of time, known as "resilience-based planning," "resilience-based response," and "resilience-based restoration." The most widely used approaches, methods, and techniques in each of these categories, as well as the future trends for improving the power system resilience are reviewed in this article. The challenges of resilience in power systems with high penetration of renewable energy sources are also discussed in each of these categories.
Hybrid AC–DC microgrid is introduced as the future distribution network to utilise both benefits of alternative and direct currents. In such hybrid microgrid, AC and DC loads, renewable-based ...distributed generators (DGs), controllable DGs and energy storage systems are connected through separate AC and DC links. An up–down operation model of such hybrid microgrid is proposed which consists of system- and device-level. In the system-level, a mixed integer linear model is suggested to balance the generation and load considering the interconnection of AC and DC subgrids for minimising total operating cost of the system in a 24-hour period. In the device-level, a controller is suggested for power converter-based resources (i.e. intergrid inverter and battery) for controlling the voltage variations in AC and DC subgrids. The effectiveness of the proposed up–down operation model is demonstrated through simulation studies on a test hybrid microgrid.
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